Probabilistic Models, Multi-agent Systems & Natural Language

Notes:

Probabilistic models are a type of mathematical model that is used to represent uncertain or random phenomena. In the context of multi-agent systems, probabilistic models can be used to represent the behavior and decision-making processes of individual agents, and to analyze the collective behavior of the system as a whole.

Multi-agent systems are systems composed of multiple independent agents that interact with each other and their environment to achieve a common goal. In such systems, the behavior and decision-making processes of individual agents may be influenced by a variety of factors, including the actions of other agents, the state of the environment, and their own internal goals and objectives.

Probabilistic models can be used to represent the uncertainty and complexity of these factors, and to analyze the behavior of the system as a whole. For example, a probabilistic model might be used to represent the probability that a particular agent will take a certain action based on the actions of other agents and the state of the environment.

Vector space and probabilistic models are two examples of statistical retrieval approaches that are used in information retrieval systems to determine the relevance of documents with respect to a user’s query.

In a vector space model, documents and queries are represented as vectors in a multidimensional space, where each dimension corresponds to a term in the document or query. The similarity between a document and a query is then determined based on the distance between their vectors in the space.

In a probabilistic model, the relationship between a document and a query is determined based on the presence or absence of certain terms in the document or query, which are considered as features. The relevance of a document is determined based on the probability that it will contain the features of the query.

Both vector space and probabilistic models use statistical information in the form of term frequencies to determine the relevance of documents with respect to a query. However, they differ in the way they represent and analyze the relationship between documents and queries.

In the field of data-driven medicine, multi-agent systems can be used to represent and analyze the complex interactions between different healthcare professionals, patients, and the healthcare system as a whole. For example, a multi-agent system might be used to represent the interactions between doctors, nurses, and patients in a hospital setting, and to analyze the factors that influence the quality and effectiveness of care.

Probabilistic models can be used in data-driven medicine to represent the uncertainty and complexity of these interactions, and to analyze the behavior of the system as a whole. For example, a probabilistic model might be used to represent the probability that a patient will adhere to a prescribed treatment plan based on the actions of healthcare professionals and the patient’s own characteristics and behavior.

Resources:

Wikipedia:

References:

See also:

Abduction & Dialog Systems | FOPC (First Order Predicate Calculus) & Dialog Systems

Speech recognition algorithm for natural language management systems under variety of accents
I Gurtueva, O Nagoeva… – E3S Web of …, 2020 – e3s-conferences.org
… The stochastic approach uses probabilistic models to remove uncertainties or incomplete information … Phoneme Fig. 1. The first level for the multi-agent system (MAS) of speech recognition … M. Wooldridge, An Introduction to Multi-Agent Systems (Wiley, Hoboken, 2009) 22 …

A Self Learning Chat-Bot From User Interactions and Preferences
P Thosani, M Sinkar, J Vaghasiya… – 2020 4th International …, 2020 – ieeexplore.ieee.org
… Technology has always been reducing human effort and hence a multi-agent system is proposed that … Reference [9] talks about how natural language generation works and how Recurrent neural … agent but when it comes to RASA it uses probabilistic models and reinforcement …

Intelligent tutoring system
AS Rathore, SK Arjaria – Utilizing educational data mining …, 2020 – igi-global.com
… Latham, Crockett, & McLean, An adaptation algorithm for an intelligent natural language tutoring system … The multi-agent system extracts relevant features of different learners and retains the same cases … The probabilistic models are used to create a conceptual model, the use of …

Intelligent software engineering in the context of agile software development: A systematic literature review
M Perkusich, LC e Silva, A Costa, F Ramos… – Information and …, 2020 – Elsevier
… We define an “intelligent technique” as a technique that explores data (from digital artifacts or domain experts) for knowledge discovery, reasoning, learning, planning, natural language processing, perception or supporting decision-making …

Research on Sentiment Classification Algorithms on Online Review
R Yan, Z Xia, Y Xie, X Wang, Z Song – Complexity, 2020 – hindawi.com
The product online review text contains a large number of opinions and emotions. In order to identify the public’s emotional and tendentious information, we present reinforcement learning models in which sentiment classification algorithms of product online review corpus are discussed …

Setting the Boundaries of the AI Landscape: An Operational Definition for the European Commission’s AI Watch
S Samoili, ML Cobo, E Gómez, G de Prato… – dmip.webs.upv.es
… task learning neural network pattern recognition probabilistic learning probabilistic model recommender system … information extraction information retrieval natural language understanding natural language generation machine … Integration and Interaction Multi-agent systems …

A knowledge graph method for hazardous chemical management: Ontology design and entity identification
X Zheng, B Wang, Y Zhao, S Mao, Y Tang – Neurocomputing, 2020 – Elsevier
… The most basic of rule-based methods are dictionary-based entity recognition. For the good performance of deep learning in natural language processing, most of the learning-based methods are implemented using deep learning …

Retrospect and Prospect of Artificial Intelligence Research in China
J Tang, S Yuan, Y Zhou – China’s e-Science Blue Book 2018, 2020 – Springer
… processing (204 persons, 13.13% of the total), social network (84 persons, 5.41% of the total), multi-agent system (61 persons … Multi-agent systems. 2312 … Science 359, 6379 (2018).Google Scholar. 2. Rosenblatt F. The perceptron: A probabilistic model for information storage and …

Polarity Analysis of Customer Reviews Based on Part-of-Speech Subcategory
AS Ghabayen, BH Ahmed – Journal of Intelligent Systems, 2020 – degruyter.com
… The classification process relies upon the analysis of the polarity features of the natural language text given by users … The linguistics-based SA divides natural language text not simply into particular constituent words and sentences …

Knowledge graph based automated generation of test cases in software engineering
A Nayak, V Kesri, RK Dubey – Proceedings of the 7th ACM IKDD CoDS …, 2020 – dl.acm.org
… Lin- guistics and the 7th International Joint Conference on Natural Language Processing (Volume 1 … Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data … An ontology-based multi-agent system for active soft- ware engineering ontology …

A Kernel Probabilistic Model for Semi-supervised Co-clustering Ensemble
Y Zhang – Journal of Intelligent Systems, 2020 – degruyter.com
… Confirm Cancel. Yinghui Zhang. A Kernel Probabilistic Model for Semi-supervised Co-clustering Ensemble … Then, a kernel probabilistic model for semi-supervised co-clustering ensemble (KPMSCE) is presented and the inference of KPMSCE is illustrated in detail …

Towards a Theory of Intentions for Human-Robot Collaboration
R Gomez, M Sridharan, H Riley – Multi-Agent Systems and Agreement …, 2020 – Springer
… EUMAS 2020, AT 2020: Multi-Agent Systems and Agreement Technologies pp 3-19 | Cite as … The executor uses probabilistic models of the uncertainty in sensing and actuation to execute each … Language: Action languages are formal models of parts of natural language used for …

A Deep Learning Cognitive Architecture: Towards a Unified Theory of Cognition
I Panella, LZ Fragonara, A Tsourdos – Proceedings of SAI Intelligent …, 2020 – Springer
… Probabilistic model – Bayes networks … Voice commands – Ability to control the system through natural language interaction … network (DLNN) framework, which will enable the parallel processing of information and will be developed as a multi-agent systems (MAS) framework …

Explanation augmented feedback in human-in-the-loop reinforcement learning
L Guan, M Verma, S Kambhampati – arXiv preprint arXiv:2006.14804, 2020 – arxiv.org
… An ideal way of conveying this infor- mation can be through natural language, but this imposes a stronger assumption of having a system … framework (Griffith et al., 2013; Cederborg et al., 2015) treats human feedback as direct policy labels and uses a probabilistic model to learn …

Specification, synthesis and validation of strategies for collaborative embedded systems
BH Schlingloff – International Symposium on Leveraging Applications of …, 2020 – Springer
… MCMAS is a tool for model checking of strategic epistemic logic with multi-agent systems … the aims of the system with user stories in controlled natural language, augmented by … used quantitative analysis methods such as stochastic simulation and probabilistic model checking …

A grey wolf optimizer for text document clustering
H Rashaideh, A Sawaie, MA Al-Betar… – Journal of Intelligent …, 2020 – degruyter.com
… Abstract. Text clustering problem (TCP) is a leading process in many key areas such as information retrieval, text mining, and natural language processing. This presents the need for a potent document clustering algorithm that …

THAI EDU SEGMENTATION USING CLUE MARKERS AND SYNTACTIC INFORMATION FROM SHALLOW PARSER
A KONGWAN, SSB KAMARUDDIN… – Journal of Theoretical and …, 2020 – jatit.org
… Keywords: Word Segmentation, EDU Segmentation, Conditional Random Field, Shallow Parser, Natural Language Processing 1. INTRODUCTION … Natural Language Processing (NLP) tasks are the essential task to achieve that purpose, especially in Thai text [1, 2] …

Multi-agent system based on the extreme learning machine and fuzzy control for intelligent energy management in microgrid
D El Bourakadi, A Yahyaouy… – Journal of Intelligent …, 2020 – degruyter.com
… Multi-Agent System Based on the Extreme Learning Machine and Fuzzy Control for Intelligent Energy Management in Microgrid … In this paper, we present a multi-agent system based on wind and photovoltaic power prediction using the extreme learning machine algorithm …

Intelligent Control Systems and Fuzzy Controllers. I. Fuzzy Models, Logical-Linguistic and Analytical Regulators
SN Vassilyev, YI Kudinov, FF Pashchenko… – Automation and Remote …, 2020 – Springer
… in the conflict environment, • application of deterministic and probabilistic models of description … scale, and at the level of group interaction of decentralized multi-agent systems … knowledge processing; • operations with partially formalized and natural language texts; • abductive …

Database Creation and Dialect-Wise Comparative Analysis of Prosodic Features for Punjabi Language
SJ Arora, R Singh – Journal of Intelligent Systems, 2020 – degruyter.com
… Robotic Systems; Natural Language Processing; AI Powered Internet of Things; Image and Video Processing and Analysis; Data Mining; Bayesian Learning; Intelligent Agents and Multi-Agent Systems. Article formats Research …

Spoken notifications in smart environments using Croatian language
R Šoi?, M Vukovi?, G Ježi? – Computer Science and Information …, 2020 – doiserbia.nb.rs
… The input text is typically received from the 33 natural language generation subsystem, while the resulting synthesized speech can be 34 reproduced … 10 Additionally, a probabilistic model is built, whose purpose is to create parameters which 11 were not present in the training …

Cognitively Motivated Query Abstraction Model Based on Associative Root-Pattern Networks
B Haddad – Journal of Intelligent Systems, 2020 – degruyter.com
… Furthermore, using natural language understanding systems, as tools for inter-cognitive infocommunications between humans and machines, which are capable of simulating query cognition; represents an important step toward supporting the co-evolution process between …

Interactive task learning via embodied corrective feedback
M Appelgren, A Lascarides – … Agents and Multi-Agent Systems, 2020 – Springer
… Autonomous Agents and Multi-Agent Systems volume 34, Article number: 54 (2020) Cite this article … Although interaction can take many forms, such as demonstration through imitation or teleoperation [6], our interest lies in approaches that make use of natural language to teach …

The Use of Natural Language Processing Approach for Converting Pseudo Code to C# Code
AT Imam, AJ Alnsour – Journal of Intelligent Systems, 2020 – degruyter.com
… Changing the currency will empty your shopping cart. Confirm Cancel. Ayad Tareq Imam and Ayman Jameel Alnsour. The Use of Natural Language Processing Approach for Converting Pseudo Code to C# Code … 1.4 Natural Language Processing …

An Improvisational Approach to Acquire Social Interactions
D Feng, S Marsella – Proceedings of the 20th ACM International …, 2020 – dl.acm.org
… The Restaurant Game [28] asked crowd workers to be a customer in a simulated virtual restaurant then built a probabilistic model of their … based language modeling with reinforcement learning to build a Chat-bot that could negotiate with a human player using natural language …

A discrete hidden Markov model for SMS spam detection
T Xia, X Chen – Applied Sciences, 2020 – mdpi.com
… HMMs are a formal foundation for building probabilistic models of linear sequence labeling problems … It is defined as a graphical probabilistic model for multivariate analysis … developed a score-based filtering mechanism in consensus of hybrid multi-agent systems with malicious …

Multimodal Systems: Taxonomy, Methods, and Challenges
MZ Baig, M Kavakli – arXiv preprint arXiv:2006.03813, 2020 – arxiv.org
… or middle agents) framework that “uses teamwork to recover a multi-agent system broker failures … Probabilistic models are used to deal with this scenario [104] … is an active field of research such as gesture recognition, speech recognition, natural language understanding, activity …

Logico-computational aspects of rationality
J van Benthem, F Liu, S Smets – … of Rationality”, M. Knauff & W …, 2020 – eprints.illc.uva.nl
… It proposes that a computer achieves intelligence if an observer using natural language cannot tell that computer apart from a human by … paradigm of computing today, not single machines. Likewise, multi-agent systems … notions of belief from richer probabilistic models …

Ensembles of text and time-series models for automatic generation of financial trading signals from social media content
OA Bari, A Agah – Journal of Intelligent Systems, 2020 – degruyter.com
… Measuring statistical impact is not the central goal. Instead, listed here are the selected implementation objectives. By utilizing natural language processing, the goal is to identify events on Twitter that influence stock prices of firms … 1.4 Natural Language Processing …

Artificial Intelligence and Machine Learning
L Mich – Handbook of e-Tourism, 2020 – Springer
… Classical AI focused on problem-solving, search and optimizations, intelligent agents, logics, knowledge representation, uncertainty, reasoning, planning and decision-making, learning models, natural language processing, computer vision, and robotics (Russell and Norvig …

Presentation of ACT/R-RBF Hybrid Architecture to Develop Decision Making in Continuous and Non-continuous Data
N Rezazadeh, T Banirostam – Journal of Intelligent Systems, 2020 – degruyter.com
… theory. Wermter [29] presented a hybrid connectionist natural language processing. Garcez … papers. One important instance is use of a cognitive neural network for learning and communicating through natural language [13]. In …

Improvements in Spoken Query System to Access the Agricultural Commodity Prices and Weather Information in Kannada Language/Dialects
TG Yadava, HS Jayanna – Journal of Intelligent Systems, 2020 – degruyter.com
De Gruyter De Gruyter …

VizCommender: Computing Text-Based Similarity in Visualization Repositories for Content-Based Recommendations
M Oppermann, R Kincaid… – IEEE Transactions on …, 2020 – ieeexplore.ieee.org
… more extreme: the title and label text may or may not be strictly related, and certainly do not have the same natural language relationships that … LDA is a probabilistic model that is first trained on bag-of-words of documents and then computes a probability distribution over k topics …

Secure fingerprint authentication using deep learning and minutiae verification
VM Praseetha, S Bayezeed, S Vadivel – Journal of Intelligent …, 2020 – degruyter.com
… A fine example is demonstrated in Ref. [8]. – Syntactic: These algorithms are based on a general grammar, like in the case of natural language processing applications. Here, the features extracted from the input data are stored as symbols in the database …

A Review of Artificial Intelligence for Games
X Fan, J Wu, L Tian – Artificial Intelligence in China, 2020 – Springer
… In [25], the authors train a probabilistic model to predict the strategy behaviors based … of SL, has been widely used in speech recognition, natural language processing, and … Gabriel I, Negru V, Zaharie D (2012) Neuroevolution based multi-agent system for micromanagement in …

Information Retrieval and Artificial Intelligence
M Boughanem, I Akermi, G Pasi… – A Guided Tour of Artificial …, 2020 – Springer
… such as Metaheuristics (evolutionary computation), game theory, multi-agent systems have been … extensively discussed in chapter “Artificial Intelligence and Natural Language” of this … Probabilistic models including BM25 (Robertson and Walker 1994), language models (Ponte …

Crossmodal attentive skill learner: learning in Atari and beyond with audio–video inputs
DK Kim, S Omidshafiei, J Pazis, JP How – … Agents and Multi-Agent Systems, 2020 – Springer
… Autonomous Agents and Multi-Agent Systems volume 34, Article number: 16 (2020) Cite this article … Previous attention-based neural architectures take advantage of both classes, for instance, to solve natural language processing problems [45]; our approach follows a similar …

Non-word Attributes’ Efficiency in Text Mining Authorship Prediction
TK Mustafa – Journal of Intelligent Systems, 2020 – degruyter.com
… Robotic Systems; Natural Language Processing; AI Powered Internet of Things; Image and Video Processing and Analysis; Data Mining; Bayesian Learning; Intelligent Agents and Multi-Agent Systems. Article formats Research …

Composing Web Services Using a Multi-Agent Framework
Y Zhao, DA Da Costa, Y Zou – IEEE Transactions on Services …, 2020 – ieeexplore.ieee.org
… Index Terms—service composition, multi-agent framework, Jadex, multilayer perceptron model, semi-natural language syntax ? 1 INTRODUCTION … [5], which analyzes grammatical structures of sentences written in natural language to extract tasks …

Model checking intelligent avionics systems for test cases generation using multi-agent systems
W Elkholy, M El-Menshawy, J Bentahar… – Expert Systems with …, 2020 – Elsevier
… Model checking. Test cases generation. Avionics. Multi-agent systems. Interpreted systems. Commitments. MCMAS+ … we model each main component as an intelligent agent that is socially able to communicate with other agents to produce a multi-agent system (MAS) where each …

Discriminative training using noise robust integrated features and refined HMM modeling
M Dua, RK Aggarwal, M Biswas – Journal of Intelligent Systems, 2020 – degruyter.com
De Gruyter De Gruyter …

Enhanced twitter sentiment analysis using hybrid approach and by accounting local contextual semantic
I Gupta, N Joshi – Journal of intelligent systems, 2020 – degruyter.com
De Gruyter De Gruyter …

A Filtering Process to Enhance Topic Detection and Labelling
A Tarifa, A Hedhili, WL Chaari – Procedia Computer Science, 2020 – Elsevier
… In fact, it is a generative probabilistic model which assumes that each document is generated … in: Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 1 … Enhancing assessment of personalized multi-agent system through convlstm …

Process mining approach to formal business process modelling and verification: a case study
S Ito, D Vym?tal, R Šperka – Journal of Modelling in Management, 2020 – emerald.com
… 5. Verification of the formal model 5.1 The correctness properties For verifying timed automata, UPPAAL uses the simplified version of TCTL as the query language. Section 3.2 stated the correctness requirements on our business process in a natural language …

Logic-based technologies for intelligent systems: State of the art and perspectives
R Calegari, G Ciatto, E Denti, A Omicini – Information, 2020 – mdpi.com
… years for commonsense reasoning formalization: there are freely available commonsense knowledge bases and natural language processing toolkits … modal logic used for formalizing, validating, and designing cognitive agents—typically, in the multi-agent systems (MAS) context …

Detecting Emergent Behavior in Scenario-Based Specifications using a Probabilistic Model
M Jahan, ZSH Abad, B Far – 2020 IEEE Tenth International …, 2020 – ieeexplore.ieee.org
… in scenario-based specifications like MSCs or UML SDs using a probabilistic model … our research in gener- ating sequence diagrams from natural language requirements documents … and BH Far, “Model based detection of implied scenarios in multi agent systems,” in Information …

BARD: A structured technique for group elicitation of Bayesian networks to support analytic reasoning
AE Nicholson, KB Korb, EP Nyberg, M Wybrow… – arXiv preprint arXiv …, 2020 – arxiv.org
Page 1. BARD: A structured technique for group elicitation of Bayesian networks to support analytic reasoning Ann E. Nicholsona,?, Kevin B. Korba, Erik P. Nyberga, Michael Wybrowa, Ingrid Zukermana, Steven Mascarob, Shreshth …

A New Feature Selection Method for Sentiment Analysis in Short Text
HMK Kumar, BS Harish – Journal of Intelligent Systems, 2020 – degruyter.com
De Gruyter De Gruyter …

Cognitive Evaluation of Machine Learning Agents
S Kadam, V Vaidya – Cognitive Systems Research – Elsevier
… AI/ML Applications, Playing Games (Atari) with Deep Q Learning, Specialized AI: Image, Speech & Text Recognition, General AI: Scene Understanding, Image Description, Generative Models; Image, Story & Music Generators, Multi Agent Systems, Swarm Robotics …

Responsible processing of crowdsourced tourism data
F Leal, B Malheiro, B Veloso… – Journal of Sustainable …, 2020 – Taylor & Francis
… (2014) use multi-agent systems to compute the … They propose a unified probabilistic model, which combines the advantages of collaborative filtering and aspect-based opinion … that permits the user model to be explicitly presented to users in natural language, empowering users …

A computational approach to analyzing and detecting trans-exclusionary radical feminists (TERFs) on Twitter
CT Lu – 2020 – digitalcommons.dartmouth.edu
… Introduction Abusive content on social media has become a more salient issue to computer scientists working in natural language processing (NLP). While work … 15 Page 17. LDA is a generative probabilistic model which can build a topic model from a corpora of text documents …

A survey of recent methods on deriving topics from Twitter: algorithm to evaluation
R Nugroho, C Paris, S Nepal, J Yang… – Knowledge and Information …, 2020 – Springer
… Jelisavc?i? et al. [46] provide an overview of popular probabilistic models used in topic modeling. Hong and Davison [42] conducted an empirical study of topic modeling methods in Twitter by comparing the performance of LDA [9] and the author–topic model [101]. Fig. 1 figure1 …

Hierarchical Argumentation Structure for Persuasive Argumentative Dialogue Generation
K Sakai, R Higashinaka, Y Yoshikawa… – … on Information and …, 2020 – search.ieice.org
… artificial agent that can se- lect abstract argumentative actions to persuade its artifi- cial interlocutor; this relied on a probabilistic model of the … The dialogue manager also updates the selected node and sends the selected action to the natural language generation (NLG) module …

Analogy-Based Approaches to Improve Software Project Effort Estimation Accuracy
V Resmi, S Vijayalakshmi – Journal of Intelligent Systems, 2020 – degruyter.com
… They are vector quantized k-means clustering and Probabilistic Model-Based Expectation-Maximization (EM) clustering. 3.2.1 Vector Quantized k-Means Clustering … 3.2.2 Probabilistic Model-Based Expectation-Maximization Algorithm …

DeComplex: Task planning from complex natural instructions by a collocating robot
P Pramanick, HB Barua, C Sarkar – arXiv preprint arXiv:2008.10084, 2020 – arxiv.org
… One of the valued features of such a cohabitant robot is that it performs tasks that are instructed in natural language. However, it is not trivial to execute the human intended tasks as natural language expressions can have large linguistic variations …

A Survey of Knowledge-based Sequential Decision Making under Uncertainty
S Zhang, M Sridharan – arXiv preprint arXiv:2008.08548, 2020 – arxiv.org
… These methods, by them- selves, do not support probabilistic models of uncertainty to- ward achieving long-term goals, whereas a lot of … Action Languages Action languages are formal models of part of natural language used for describing transition dia- grams, and many action …

Optimizing the self-organizing team size using a genetic algorithm in agile practices
W Almadhoun, M Hamdan – Journal of Intelligent Systems, 2020 – degruyter.com
De Gruyter De Gruyter …

Automatically assess day similarity using visual lifelogs
K El Asnaoui, P Radeva – Journal of Intelligent Systems, 2020 – degruyter.com
De Gruyter De Gruyter …

Adaptive protocol generation for group collaborative in smart medical waste transportation
W Liu, J Guo, F Yao, D Chen – Future Generation Computer Systems, 2020 – Elsevier
… In terms of Multi-Agent Systems (MAS), “they are especially suited to develop software systems that are decentralized, can deal flexibly with dynamic conditions and are open to system components that come and go” [5]. These properties make agent-based techniques valuable …

A flame detection method based on novel gradient features
Z Liping, L Hongqi, W Fenghui, L Jie, S Ali… – Journal of Intelligent …, 2020 – degruyter.com
… 2 Related Works. The typical approaches to flame detection consist of a probabilistic model, a background subtraction model, and a Markov model [1, 2, 14, 17], in which edge, color, and shape are the most common features, respectively. Gomes et al …

Proximal support vector machine-based hybrid approach for edge detection in noisy images
SK Jain, D Kumar, M Thakur, RK Ray – Journal of Intelligent Systems, 2020 – degruyter.com
De Gruyter De Gruyter …

Implementation of Improved Ship-Iceberg Classifier Using Deep Learning
A Rane, V Sangili – Journal of Intelligent Systems, 2020 – degruyter.com
… Robotic Systems; Natural Language Processing; AI Powered Internet of Things; Image and Video Processing and Analysis; Data Mining; Bayesian Learning; Intelligent Agents and Multi-Agent Systems. Article formats Research …

Adaptive embedded systems: a systematic review
F Boutekkouk – International Journal of Autonomous and …, 2020 – inderscienceonline.com
… modelling as fuzzy logic. At the design level, a variety of models can be used including component models, architecture description languages (ADLs), automata, probabilistic models, formal models, etc. Adaptivity can also be …

A review of modelling and verification approaches for computational biology
S Konur – 2020 – bradscholars.brad.ac.uk
… 11], distributed systems [12], network protocols [13], stochastic systems [14], multi-agent systems [15, 16 … PRISM [109] is the most widely used probabilistic model checking tool for formal … multi-terminal) binary decision diagrams (BDDs) to reduce the size of probabilistic models …

Binary genetic swarm optimization: A combination of GA and PSO for feature selection
M Ghosh, R Guha, I Alam, P Lohariwal… – Journal of Intelligent …, 2020 – degruyter.com
De Gruyter De Gruyter …

A survey of swarm and evolutionary computing approaches for deep learning
A Darwish, AE Hassanien, S Das – Artificial Intelligence Review, 2020 – Springer
Deep learning (DL) has become an important machine learning approach that has been widely successful in many applications. Currently, DL is one of the best.

Speech technology for healthcare: Opportunities, challenges, and state of the art
S Latif, J Qadir, A Qayyum, M Usama… – IEEE Reviews in …, 2020 – ieeexplore.ieee.org
… They are also extended for natural language processing (NLP) and speech processing … They are directed probabilistic models and can model joint distribution using the following chain-rule: p(x) = T ? t=1 p(xt|x1, …. xt?1; ?), (5) …

Gesture Planning and Execution for Anchoring between Multi-Embodiment Robots in Decentralized Settings
K Gulzar – 2020 – aaltodoc.aalto.fi
Page 1. r a zl u G marr u h K d e zil art ne c e D ni st o b o R t ne mi d o b m E-itl u M nee wt e b g nir o h c n A r of n oit u c e x E d n a g ni nn al P er ut s e G s g nitt eS yti sr e vi n U otla A 0 2 0 2 ut se G uc ex E e wt eb to bo R nit te S r a zl u G marr u h K …

Scen@ rist: an approach for verifying self-adaptive systems using runtime scenarios
R Gadelha, L Vieira, D Monteiro, F Vidal… – Software Quality …, 2020 – Springer
… 2005; Sadot et al. 2008; Kugler 2013), multi-agent systems (Whittle and Schumann 2006; Moshirpour et al … (2017) presented Lotus@Runtime, an open-source and extensible tool that provides support for software monitoring and verification using probabilistic models, which are …

Common Sense Reasoning in Autonomous Artificial Intelligent Agents Through Mobile Computing
AZ Henderson – 2020 – dash.harvard.edu
… explain their conclusions. It can improve human-computer interaction, resolve ambiguities within natural language processing, and computer vision, and allow for automated planning … including common sense reasoning, planning, machine learning, natural language …

Student Subtyping via EM-Inverse Reinforcement Learning.
X Yang, G Zhou, M Taub, R Azevedo, M Chi – International Educational Data …, 2020 – ERIC
… different scenarios. Based on how the rewards are inferred, existing IRL algo- rithms can be generalized into two categories: maximum margin-based methods and probabilistic model-based meth- ods. Specifically, maximum …

Machine learning-based design concept evaluation
B Camburn, Y He… – Journal of …, 2020 – asmedigitalcollection.asme.org
… from these foundations and related work by the authors [3,9,10], which includes assessing morphological differences in large idea sets as a whole [3] and presenting an approach for the automated assessment of design concepts that are written in natural language without any …

Effective distributed representations for academic expert search
M Berger, J Zavrel, P Groth – arXiv preprint arXiv:2010.08269, 2020 – arxiv.org
… Probabilistic models A driving force behind ex- pertise retrieval research was the launch of the TREC Enterprise Track in 2005 (Craswell et al., 2005). This evaluation campaign led to the emer- gence of probabilistic models, in …

Geometric Extensions of Neural Processes
AN Carr – 2020 – scholarsarchive.byu.edu
… These data are ubiquitous in modern data analysis, and are often encountered in biological systems, social networks, or natural language processing. The ability to perform regression … from the degree matrix L = D ? A. This formulation, common in multi-agent systems and …

Design and Evaluation of Outlier Detection Based on Semantic Condensed Nearest Neighbor
MR Batchanaboyina, N Devarakonda – Journal of Intelligent Systems, 2020 – degruyter.com
De Gruyter De Gruyter …

Automatic speech recognition: a survey
M Malik, MK Malik, K Mehmood… – Multimedia Tools and …, 2020 – Springer
Recently great strides have been made in the field of automatic speech recognition (ASR) by using various deep learning techniques. In this study, we prese.

Robots That Use Language: A Survey
S Tellex, N Gopalan, H Kress-Gazit, C Matuszek – 2020 – h2r1.cs.brown.edu
… Later work (88) discussed controlled natural language as a way to repair missing information through explicit clarification. Nyga et al. (135) used a similar probabilistic model for using relational knowledge to fill in gaps for aspects of the language missing from the workspace …

Uncertainty-aware specification and analysis for hardware-in-the-loop testing of cyber-physical systems
SY Shin, K Chaouch, S Nejati, M Sabetzadeh… – Journal of Systems and …, 2020 – Elsevier
JavaScript is disabled on your browser. Please enable JavaScript to use all the features on this page. Skip to main content Skip to article …

Optimizing integrated features for Hindi automatic speech recognition system
M Dua, RK Aggarwal, M Biswas – Journal of Intelligent Systems, 2020 – degruyter.com
De Gruyter De Gruyter …

A case study on the Big 4 Firms: Impact of Artificial Intelligence on the work of external auditors
N Cahyadi, R van der Wal – thesis.eur.nl
… NLP is a field of AI that relates to the natural language data, which includes … the machines were given pre-defined probabilistic models which are then used to make an inference in … utilizes the multi-agent systems where it aims to solve complex problems, typically using a large …

Artificial intelligence techniques for stability analysis and control in smart grids: Methodologies, applications, challenges and future directions
Z Shi, W Yao, Z Li, L Zeng, Y Zhao, R Zhang, Y Tang… – Applied Energy, 2020 – Elsevier

A New Algorithm Based on Magic Square and a Novel Chaotic System for Image Encryption
RH AL-Hashemy, SA Mehdi – Journal of Intelligent Systems, 2020 – degruyter.com
De Gruyter De Gruyter …

ILLUSTRATED COMPUTATIONAL INTELLIGENCE: Examples and Applications
PS SAJJA – 2020 – books.google.com
… machines, and processes • Medical diagnosing • Financial analysis • Planning, control, and monitoring Mundane tasks • Perception and vision • Video abstraction • Image identification/ understanding • Language generation, translation and Natural Language Processing (NLP …

Towards a hybrid formal analysis technique for safety-critical software architectures
A Boucherit, LM Castro, O Hasan, A Khababa – ohasan.seecs.nust.edu.pk
Page 1. Int. J. Critical Computer-Based Systems, Vol. x, No. x, xxxx 1 Towards a hybrid formal analysis technique for safety-critical software architectures Ammar Boucherit* Computer Science Department, University of El-Oued …

Handwritten Indic script recognition based on the Dempster–Shafer theory of evidence
A Mukhopadhyay, PK Singh, R Sarkar… – Journal of Intelligent …, 2020 – degruyter.com
De Gruyter De Gruyter …

Reinforcement Learning
O Buffet, O Pietquin, P Weng – A Guided Tour of Artificial Intelligence …, 2020 – Springer
… But probabilistic models can also be employed to represent stochastic dynamics … 2009), natural language parsers (Neu and Szepesvari 2009) or dialogue systems (El Asri et al … were proposed to tackle this degeneracy issue, differing on whether a probabilistic model is assumed …

Combining Text Analysis and Concept Mapping for Conceptual Model Development
K Hanson – 2020 – shareok.org
… regularities in text data in supervised, unsupervised, or semi-supervised methods, all in the context of natural language processing (Wang, 2017) … According to Blei et al. (2003, p. 1), “Latent Dirichlet Allocation (LDA) is a generative probabilistic model of a corpus.” The term …

Symbolic learning and reasoning with noisy data for probabilistic anchoring
PZ Dos Martires, N Kumar, A Persson… – Frontiers in Robotics …, 2020 – ncbi.nlm.nih.gov
… Some notable refinements include the integration of conceptual spaces (Chella et al., 2003, 2004), the addition of bottom-up anchoring (Loutfi et al., 2005), extensions for multi-agent systems (LeBlanc and Saffiotti, 2008), considerations for non-traditional sensing modalities and …

Real-Time Human Activity Generation using Bidirectional Long Short Term Memory Networks
V Aswal, V Sreeram, A Kuchik… – 2020 4th International …, 2020 – ieeexplore.ieee.org
… series activities such as stock prediction, weather prediction, natural language processing, etc … whereas in [14], the LSTM based predictor outperformed probabilistic models such as … 21st International Conference on Principles and Practice of Multi-Agent Systems, PRIMA, 2018 …

Intelligent Systems for Structural Damage Assessment
E Vrochidou, PF Alvanitopoulos… – Journal of Intelligent …, 2020 – degruyter.com
De Gruyter De Gruyter …

Blind Restoration Algorithm Using Residual Measures for Motion-Blurred Noisy Images
M Shah, UD Dalal – Journal of Intelligent Systems, 2020 – degruyter.com
De Gruyter De Gruyter …

License plate recognition in urban road based on vehicle tracking and result integration
L Zhu, S Wang, C Li, Z Yang – Journal of Intelligent Systems, 2020 – degruyter.com
De Gruyter De Gruyter …

Enriching documents by linking salient entities and lexical-semantic expansion
M Pourvali, S Orlando – Journal of Intelligent Systems, 2020 – degruyter.com
… 2 Related Work. Given a plain text, EL aims at identifying the small fragments of text (also called spots or mentions) possibly referring to any named entity that is listed in a given knowledge base like Wikipedia. The ambiguity of natural language makes it a nontrivial task …

Illustrated Computational Intelligence
PS Sajja – Springer
Page 1. Studies in Computational Intelligence 931 Priti Srinivas Sajja Illustrated Computational Intelligence Examples and Applications Page 2. Studies in Computational Intelligence Volume 931 Series Editor Janusz Kacprzyk, Polish Academy of Sciences, Warsaw, Poland …

Video steganography using knight tour algorithm and LSB method for encrypted data
ZS Younus, GT Younus – Journal of Intelligent Systems, 2020 – degruyter.com
De Gruyter De Gruyter …

Enhancing Entrepreneurship Using High-Resolution Innovation Network Interventions
K Koehler – Available at SSRN 3670239, 2020 – papers.ssrn.com
Page 1. 1 ENHANCING ENTREPRENEURSHIP USING HIGH-RESOLUTION INNOVATION NETWORK INTERVENTIONS Working Paper August 9, 2020 Karl A. Koehler, Consultant, Santa Fe, NM Email: kkoehlerpi@gmail.com Abstract …

M-HMOGA: a new multi-objective feature selection algorithm for handwritten numeral classification
R Guha, M Ghosh, PK Singh, R Sarkar… – Journal of Intelligent …, 2020 – degruyter.com
De Gruyter De Gruyter …

Artificial intelligence within the interplay between natural and artificial computation: Advances in data science, trends and applications
JM Górriz, J Ramírez, A Ortíz, FJ Martínez-Murcia… – Neurocomputing, 2020 – Elsevier

Harmony search algorithm for patient admission scheduling problem
IA Doush, MA Al-Betar, MA Awadallah… – Journal of Intelligent …, 2020 – degruyter.com
De Gruyter De Gruyter …

Combined multi-agent method to control inter-department common events collision for university courses timetabling
J Nourmohammadi-Khiarak… – Journal of Intelligent …, 2020 – degruyter.com
… The primary solution for a multi-agent system is earned based on usage of a marketplace and an artificial currency … Also, a multi-agent system consisting of a combined heuristic that includes graph coloring heuristics and local search was proposed [29]. In Ref …

Discriminating Healthy Wheat Grains from Grains Infected with Fusarium graminearum Using Texture Characteristics of Image-Processing Technique …
Y Abbaspour-Gilandeh… – Journal of Intelligent …, 2020 – degruyter.com
De Gruyter De Gruyter …

LIMEtree: Interactively Customisable Explanations Based on Local Surrogate Multi-output Regression Trees
K Sokol, P Flach – arXiv preprint arXiv:2005.01427, 2020 – arxiv.org
… could interactively explain their nuances and decisions in a process that is intuitive to humans: for example, a voice-enabled natural language conversation … Section 3. The LIME algorithm trains a local surrogate used to explain an image x for a black-box probabilistic model f by …

Artificial Intelligence in the Creative Industries: A Review
N Anantrasirichai, D Bull – arXiv preprint arXiv:2007.12391, 2020 – arxiv.org
… Convolutional Neural Network, GAN: Generative Adversarial Network RNN: Recurrent Neural Network, RL: Reinforcement Learning, PM: Probabilistic model BERT: Bidirectional … This can be achieved through natural language processing (NLP) and text mining techniques [33] …

Improved adaptive neuro-fuzzy inference system using gray wolf optimization: A case study in predicting biochar yield
AA Ewees, M Abd Elaziz – Journal of Intelligent Systems, 2020 – degruyter.com
De Gruyter De Gruyter …

Meta-Active Learning for Node Response Prediction in Graphs
T Iwata – arXiv preprint arXiv:2010.05387, 2020 – arxiv.org
Page 1. META-ACTIVE LEARNING FOR NODE RESPONSE PREDICTION IN GRAPHS APREPRINT Tomoharu Iwata NTT Communication Science Laboratories ABSTRACT Meta-learning is an important approach to improve …

Thirty years of machine learning: The road to Pareto-optimal wireless networks
J Wang, C Jiang, H Zhang, Y Ren… – … Surveys & Tutorials, 2020 – ieeexplore.ieee.org
… Future wireless networks may hence be expected to benefit from intelligent multi-agent systems … ML schemes regained researchers’ attention leading to a range of beneficial probabilistic models … in a range of fields including computer vision, natural language processing (NLP …

Comprehensive review of deep reinforcement learning methods and applications in economics
A Mosavi, Y Faghan, P Ghamisi, P Duan, SF Ardabili… – Mathematics, 2020 – mdpi.com
The popularity of deep reinforcement learning (DRL) applications in economics has increased exponentially. DRL, through a wide range of capabilities from reinforcement learning (RL) to deep learning (DL), offers vast opportunities for handling sophisticated dynamic economics …

Selector: Pso as model selector for dual-stage diabetes network
R Cheruku, DR Edla – Journal of Intelligent Systems, 2020 – degruyter.com
De Gruyter De Gruyter …

A 4D trajectory prediction model based on the BP neural network
ZJ Wu, S Tian, L Ma – Journal of Intelligent Systems, 2020 – degruyter.com
De Gruyter De Gruyter …

Automatic Genetic Fuzzy c-Means
K Jebari, A Elmoujahid, A Ettouhami – Journal of Intelligent Systems, 2020 – degruyter.com
De Gruyter De Gruyter …

A Framework for Image Alignment of TerraSAR-X Images Using Fractional Derivatives and View Synthesis Approach
B Sirisha, B Sandhya, CS Paidimarry… – Journal of Intelligent …, 2020 – degruyter.com
De Gruyter De Gruyter …

Feature pair index graph for clustering
N Karthika, B Janet – Journal of Intelligent Systems, 2020 – degruyter.com
De Gruyter De Gruyter …

Modeling and optimization of a liquid flow process using an artificial neural network-based flower pollination algorithm
P Dutta, A Kumar – Journal of Intelligent Systems, 2020 – degruyter.com
De Gruyter De Gruyter …

A corroborative approach to verification and validation of human–robot teams
M Webster, D Western, D Araiza-Illan… – … Journal of Robotics …, 2020 – journals.sagepub.com
We present an approach for the verification and validation (V&V) of robot assistants in the context of human–robot interactions, to demonstrate their trustworthiness through corroborative evidence …

Mitigating Uncertainty in Big Data and Artificial Intelligence Applications
RH Hariri – 2020 – search.proquest.com
… 71 5.2.1. Early-Stage Alzheimer’s Disease 71 5.2.2. Multi-Agent Systems 71 … Because many requirements and artifacts are written in natural language, natural language processing (NLP) … CAL is a multi-agent system (MAS) with an agent to interact with patient to monitor …

A genetic algorithm approach for group recommender system based on partial rankings
R Meena, KK Bharadwaj – Journal of Intelligent Systems, 2020 – degruyter.com
De Gruyter De Gruyter …

Distributed multi-agent bidding-based approach for the collaborative mapping of unknown indoor environments by a homogeneous mobile robot team
A Hentout, A Maoudj, N Kaid-Youcef… – Journal of Intelligent …, 2020 – degruyter.com
… HMIA. 3.3 Interaction Between the Agents of the Control System. A key component to a multi-agent system is the mechanism that allows agents to interact [1]. This interaction is implemented through messages exchange protocol …

Clay-Based Brick Porosity Estimation Using Image Processing Techniques
S Jida, H Ouallal, B Aksasse, M Ouanan… – Journal of Intelligent …, 2020 – degruyter.com
De Gruyter De Gruyter …

Dual Learning
T Qin – 2020 – Springer
… with applications to language understanding, speech processing and computer vision), game theory and multi-agent systems (with applications … breakthroughs in different areas in recent years, including computer vision, speech recognition, natural language processing, game …

Group recommender systems–an evolutionary approach based on multi-expert system for consensus
R Meena, S Minz – Journal of Intelligent Systems, 2020 – degruyter.com
De Gruyter De Gruyter …

A Bayesian multiresolution approach for noise removal in medical magnetic resonance images
S Sahu, HV Singh, B Kumar, AK Singh – Journal of Intelligent …, 2020 – degruyter.com
De Gruyter De Gruyter …

A survey on autonomous vehicle control in the era of mixed-autonomy: From physics-based to ai-guided driving policy learning
X Di, R Shi – arXiv preprint arXiv:2007.05156, 2020 – arxiv.org
… Due to this coupling among agents, the mixed transportation system is a multi-agent system (MAS) – a widely used term in the control and robotics community. Specifically, we call it a “multi-vehicle system (MVS).” Definition 2.1 …

A hybrid grey wolf optimiser algorithm for solving time series classification problems
H Al Nsour, M Alweshah, AI Hammouri… – Journal of Intelligent …, 2020 – degruyter.com
De Gruyter De Gruyter …

An Improved Particle Swarm Optimization Algorithm for Global Multidimensional Optimization
R Fajr, A Bouroumi – Journal of Intelligent Systems, 2020 – degruyter.com
De Gruyter De Gruyter …

Community detection in node-attributed social networks: a survey
P Chunaev – Computer Science Review, 2020 – Elsevier

Early detection of Parkinson’s disease by using SPECT imaging and biomarkers
G Pahuja, TN Nagabhushan, B Prasad – Journal of Intelligent …, 2020 – degruyter.com
De Gruyter De Gruyter …

Efficient classification of DDoS attacks using an ensemble feature selection algorithm
KJ Singh, T De – Journal of Intelligent Systems, 2020 – degruyter.com
De Gruyter De Gruyter …

A one-pass approach for slope and slant estimation of tri-script handwritten words
SK Bera, R Kar, S Saha, A Chakrabarty… – Journal of Intelligent …, 2020 – degruyter.com
De Gruyter De Gruyter …

Symbolic Learning and Reasoning with Noisy Data for Probabilistic Anchoring
PZD Martires, N Kumar, A Persson, A Loutfi… – arXiv preprint arXiv …, 2020 – arxiv.org
… Some notable refinements include the integration of conceptual spaces (Chella et al., 2003, 2004), the addition of bottom-up anchoring (Loutfi et al., 2005), extensions for multi-agent systems (LeBlanc and Saffiotti, 2008), considerations for non-traditional sensing modalities and …

Software Effort Estimation Using Modified Fuzzy C Means Clustering and Hybrid ABC-MCS Optimization in Neural Network
H Azath, M Mohanapriya… – Journal of Intelligent …, 2020 – degruyter.com
De Gruyter De Gruyter …

An improved robust fuzzy algorithm for unsupervised learning
A Dik, K Jebari, A Ettouhami – Journal of Intelligent Systems, 2020 – degruyter.com
De Gruyter De Gruyter …

Universal liver extraction algorithm: an improved Chan–vese model
SK Siri, MV Latte – Journal of Intelligent Systems, 2020 – degruyter.com
De Gruyter De Gruyter …

An Optimized K-Harmonic Means Algorithm Combined with Modified Particle Swarm Optimization and Cuckoo Search Algorithm
A Bouyer, N Farajzadeh – Journal of Intelligent Systems, 2020 – degruyter.com
De Gruyter De Gruyter …

A novel weakest t-norm based fuzzy fault tree analysis through qualitative data processing and its application in system reliability evaluation
M Kumar – Journal of Intelligent Systems, 2020 – degruyter.com
De Gruyter De Gruyter …

Robotics and Artificial Intelligence
M Ghallab, F Ingrand – A Guided Tour of Artificial Intelligence Research, 2020 – Springer
Robotics is an interdisciplinary research field leveraging on control theory, mechanical engineering, electronic engineering and computer science. It aims at designing machines able to perceive, move…

Oppositional gravitational search algorithm and artificial neural network-based classification of kidney images
SMK Chaitanya, PR Kumar – Journal of Intelligent Systems, 2020 – degruyter.com
De Gruyter De Gruyter …

AGCS Technique to Improve the Performance of Neural Networks
KK Katha, S Pabboju – Journal of Intelligent Systems, 2020 – degruyter.com
De Gruyter De Gruyter …

Cloud Security: LKM and Optimal Fuzzy System for Intrusion Detection in Cloud Environment
SI Shyla, SS Sujatha – Journal of Intelligent Systems, 2020 – degruyter.com
De Gruyter De Gruyter …

Integrating Recognition and Decision Making to Close the Interaction Loop for Autonomous Systems
R Freedman – 2020 – scholarworks.umass.edu
Page 1. University of Massachusetts Amherst ScholarWorks@UMass Amherst Doctoral Dissertations Dissertations and Theses July 2020 Integrating Recognition and Decision Making to Close the Interaction Loop for Autonomous Systems Richard Freedman …

Image Compression Based on Block SVD Power Method
K El Asnaoui – Journal of Intelligent Systems, 2020 – degruyter.com
De Gruyter De Gruyter …

Extreme Learning Machine for Credit Risk Analysis
MH Qasem, L Nemer – Journal of Intelligent Systems, 2020 – degruyter.com
De Gruyter De Gruyter …

Opposition intensity-based cuckoo search algorithm for data privacy preservation
GK Shailaja, CVG Rao – Journal of Intelligent Systems, 2020 – degruyter.com
De Gruyter De Gruyter …

Predict forex trend via convolutional neural networks
YC Tsai, JH Chen, JJ Wang – Journal of Intelligent Systems, 2020 – degruyter.com
De Gruyter De Gruyter …

An Efficient Technique for Three-Dimensional Image Visualization Through Two-Dimensional Images for Medical Data
G Gunasekaran, M Venkatesan – Journal of Intelligent Systems, 2020 – degruyter.com
De Gruyter De Gruyter …

Distributed Load Testing by Modeling and Simulating User Behavior
CI Parrott – 2020 – digitalcommons.lsu.edu
… System(s) Systems which are comprised of humans and ma- chines MAS Multi-Agent System(s) Systems which are comprised of human Agents and machine Agents working toward a common goal N/A Model A mathematical representation of an entity or a Sys- tem …

Hybridizing the cuckoo search algorithm with different mutation operators for numerical optimization problems
BH Abed-Alguni, DJ Paul – Journal of Intelligent Systems, 2020 – degruyter.com
De Gruyter De Gruyter …

Speech Signal Compression Algorithm Based on the JPEG Technique
TA Hassan, RH Al-Hashemy, RI Ajel – Journal of Intelligent Systems, 2020 – degruyter.com
De Gruyter De Gruyter …

Texture feature extraction using intuitionistic fuzzy local binary pattern
MD Ansari, SP Ghrera, AR Mishra – Journal of Intelligent Systems, 2020 – degruyter.com
De Gruyter De Gruyter …

A color image encryption technique based on bit-level permutation and alternate logistic maps
A Bisht, M Dua, S Dua, P Jaroli – Journal of Intelligent Systems, 2020 – degruyter.com
De Gruyter De Gruyter …

A hybrid of deep CNN and bidirectional LSTM for automatic speech recognition
V Passricha, RK Aggarwal – Journal of Intelligent Systems, 2020 – degruyter.com
De Gruyter De Gruyter …

Fault Signal Recognition in Power Distribution System using Deep Belief Network
TCS Rao, SST Ram… – Journal of Intelligent …, 2020 – degruyter.com
… by some of the researchers by developing map-reduce framework [12], rough set theory [12], wavelet transformation [24] and iterative state estimation approach [8]. In fact, those methods are considered as web mining techniques, probabilistic models, domain transformation …

FCNB: Fuzzy correlative naïve bayes classifier with MapReduce framework for big data classification
C Banchhor, N Srinivasu – Journal of Intelligent Systems, 2020 – degruyter.com
De Gruyter De Gruyter …

Bot recognition in a Web store: An approach based on unsupervised learning
S Rovetta, G Suchacka, F Masulli – Journal of Network and Computer …, 2020 – Elsevier
… Example probabilistic models include Bayesian approaches (Stassopoulou and Dikaiakos, 2009; Suchacka and Sobków, 2015), as well as Markov models based on request arrival patterns (Lu and Yu, 2006) and requested resource types (Doran and Gokhale, 2016; Suchacka …

Fuzzy Adaptive Genetic Algorithm for Improving the Solution of Industrial Optimization Problems
M Vannucci, V Colla, S Dettori… – Journal of Intelligent …, 2020 – degruyter.com
De Gruyter De Gruyter …

Opinion Mining on Digital Media Data: Advancing State-of-the-art Methods with Deep Learning
W Quan – 2020 – search.proquest.com
… natural language understanding [2]. NLP is the attempt to extract a fuller meaning representation from text … [18] which obtains new state-of-the-art results on eleven natural language processing tasks, we can see the research direction in the field …

An Efficient Quality Inspection of Food Products Using Neural Network Classification
SSE Ali, SA Dildar – Journal of Intelligent Systems, 2020 – degruyter.com
De Gruyter De Gruyter …

i-Vector-Based Speaker Verification on Limited Data Using Fusion Techniques
TRJ Kumari, HS Jayanna – Journal of Intelligent Systems, 2020 – degruyter.com
… The speaker verification system contains different types of pattern-matching techniques like template matching, probabilistic model and artificial neural network. The nearest-neighbor vector quantization (VQ) belongs to template …

iCORPP: Interleaved Commonsense Reasoning and Probabilistic Planning on Robots
S Zhang, P Stone – arXiv preprint arXiv:2004.08672, 2020 – arxiv.org
Page 1. iCORPP: Interleaved Commonsense Reasoning and Probabilistic Planning on Robots Shiqi Zhang1, and Peter Stone2 1 SUNY Binghamton 2 UT Austin zhangs@binghamton.edu; pstone@cs.utexas.edu Abstract Robot …

Prediction of user future request utilizing the combination of both ANN and FCM in web page recommendation
V Raju, N Srinivasan – Journal of Intelligent Systems, 2020 – degruyter.com
De Gruyter De Gruyter …

Noise Reduction Using Modified Wiener Filter in Digital Hearing Aid for Speech Signal Enhancement
MA Kumar, KM Chari – Journal of Intelligent Systems, 2020 – degruyter.com
De Gruyter De Gruyter …

Histopathological Image Segmentation Using Modified Kernel-Based Fuzzy C-Means and Edge Bridge and Fill Technique
FM Karobari, HN Suresh – Journal of Intelligent Systems, 2020 – degruyter.com
De Gruyter De Gruyter …

Linear Regression Supporting Vector Machine and Hybrid LOG Filter-Based Image Restoration
DK Basha, T Venkateswarlu – Journal of Intelligent Systems, 2020 – degruyter.com
De Gruyter De Gruyter …

MODEL-TO-MODEL TRANSFORMATION OF NUCLEAR INDUSTRY I&C LOGIC TO ASSIST MODEL CHECKING
P Biswas – 2020 – trepo.tuni.fi
Page 1. Prasun Biswas MODEL-TO-MODEL TRANSFORMATION OF NUCLEAR INDUSTRY I&C LOGIC TO ASSIST MODEL CHECKING Master Thesis Faculty of Engineering and Natural Sciences Examiner: Prof. Eric Coatanea Examiner: Prof. Valeriy Vyatkin April, 2020 …

Set of Experience and Decisional DNA: Experience-Based Knowledge Structures
C Sanin, E Szczerbicki – Knowledge Management and Engineering with …, 2020 – Springer
This chapter presents a description of Set of Experience Knowledge Structure (SOEKS) and Decisional DNA (DDNA), argumentation for a knowledge representation, composition, configuration and metrics….

Predicting Automatic Trigger Speed for Vehicle-Activated Signs
D Jomaa, S Yella – Journal of Intelligent Systems, 2020 – degruyter.com
De Gruyter De Gruyter …

An integrated intuitionistic fuzzy AHP and TOPSIS approach to evaluation of outsource manufacturers
C Kahraman, B Öztay?i, SÇ Onar – Journal of Intelligent Systems, 2020 – degruyter.com
De Gruyter De Gruyter …

Development of a two-stage segmentation-based word searching method for handwritten document images
S Malakar, M Ghosh, R Sarkar… – Journal of Intelligent …, 2020 – degruyter.com
De Gruyter De Gruyter …

Simulating the impact of pairing on Agile software development projects: A multi-agent approach: A thesis submitted in partial fulfilment of the requirements for the …
Z Wang – 2020 – researcharchive.lincoln.ac.nz
… has not been widely researched. A multi-agent system is used to simulate the Scrum environment … set of technical practices for the delivery of software. Keywords: Scrum, team dynamics, agent-based modelling, multi-agent system, team strategies, solo …

Tangramob: an agent-based simulation framework for validating urban smart mobility solutions
F Corradini, F De Angelis, A Polini… – Journal of Intelligent …, 2020 – degruyter.com
De Gruyter De Gruyter …

A blind medical image watermarking for secure e-healthcare application using crypto-watermarking system
P Aparna, PVV Kishore – Journal of Intelligent Systems, 2020 – degruyter.com
De Gruyter De Gruyter …

Machine learning models for secure data analytics: A taxonomy and threat model
R Gupta, S Tanwar, S Tyagi, N Kumar – Computer Communications, 2020 – Elsevier
JavaScript is disabled on your browser. Please enable JavaScript to use all the features on this page. Skip to main content Skip to article …

A session-based song recommendation approach involving user characterization along the play power-law distribution
D Sánchez-Moreno, VF López Batista… – Complexity, 2020 – hindawi.com
In recent years, streaming music platforms have become very popular mainly due to the huge number of songs these systems make available to users. This enormous availability means that recommendation mechanisms that help users to select the music they like need to be incorporated …

Towards Socially Interactive Agents: Learning Generative Models of Social Interactions Via Crowdsourcing
D Feng – 2020 – search.proquest.com
Page 1. 8/31/20 Page 2. Page 3. Towards Socially Interactive Agents: Learning Generative Models of Social Interactions via Crowdsourcing A Dissertation Presented by Dan Feng to Khoury College of Computer Sciences in partial fulfillment of the requirements for the degree of …

Deep cnn combined with relevance feedback for trademark image retrieval
L Pinjarkar, M Sharma, S Selot – Journal of Intelligent Systems, 2020 – degruyter.com
De Gruyter De Gruyter …

Sparse Decomposition Technique for Segmentation and Compression of Compound Images
VN Manju, AL Fred – Journal of Intelligent Systems, 2020 – degruyter.com
De Gruyter De Gruyter …

Optimizing Software Modularity with Minimum Possible Variations
A Prajapati, JK Chhabra – Journal of Intelligent Systems, 2020 – degruyter.com
De Gruyter De Gruyter …

An efficient lossless ROI image compression using wavelet-based modified region growing algorithm
P Sreenivasulu, S Varadarajan – Journal of Intelligent Systems, 2020 – degruyter.com
De Gruyter De Gruyter …

Gbest-Guided Artificial Bee Colony Optimization Algorithm-Based Optimal Incorporation of Shunt Capacitors in Distribution Networks under Load Growth
M Dixit, P Kundu, HR Jariwala – Journal of Intelligent Systems, 2020 – degruyter.com
De Gruyter De Gruyter …

An overview of segmentation algorithms for the analysis of anomalies on medical images
SN Kumar, AL Fred, PS Varghese – Journal of Intelligent Systems, 2020 – degruyter.com
De Gruyter De Gruyter …

Overview of deep reinforcement learning in partially observable multi-agent environment of competitive online video games
J Louhio – 2020 – helda.helsinki.fi
… deep reinforcement learning, competitive online video games, POMDP, multi-agent systems Thesis for the Algorithms, Data Analytics and Machine Learning subprogramme … the non-stationary nature of the learning environment. With multi-agent systems …

A modified Jaya algorithm for mixed-variable optimization problems
P Singh, H Chaudhary – Journal of Intelligent Systems, 2020 – degruyter.com
De Gruyter De Gruyter …

Leaf disease segmentation from agricultural images via hybridization of active contour model and OFA
MGS Jayanthi, DR Shashikumar – Journal of Intelligent Systems, 2020 – degruyter.com
De Gruyter De Gruyter …

Business Intelligence & Big Data: 14ème Edition de la conference EDA Tanger, Maroc
H Badir, F Bentayeb, O Boussaid – 2020 – books.google.com
… Distributed RFID Multi-Agent System for Healthcare Hospitals Amjad Rattrout, Fadi Abu Rob, Hassan Badir . . . . . Linked Open Data pour les Entrepôts de Données: Opportunité et Défis Nabila Berkani, Selma Khouri, Ladjel Bellatreche …

Using an Efficient Optimal Classifier for Soil Classification in Spatial Data Mining Over Big Data
A Manjula, G Narsimha – Journal of Intelligent Systems, 2020 – degruyter.com
De Gruyter De Gruyter …

A novel bio-inspired algorithm based on social spiders for improving performance and efficiency of data clustering
RC Thalamala, AVS Reddy, B Janet – Journal of Intelligent Systems, 2020 – degruyter.com
De Gruyter De Gruyter …

Improving Image Search through MKFCM Clustering Strategy-Based Re-ranking Measure
AK Naveena, NK Narayanan – Journal of Intelligent Systems, 2020 – degruyter.com
De Gruyter De Gruyter …

Fuzzy Logic Based Efficient Load Management Scheme in Vehicle-To-Grid (V2G) Environments
WL Lambert – 2020 – search.proquest.com
… 2.5 Bayesian Classification 17 v Page 6. 2.5.1 Probabilistic Model 19 2.6 Summary 20 … The main advantage of using fuzzy logic is to formalize human reasoning into natural language in order to 2 Page 15 … Likewise, [33] used a multi-agent system (MAS) consisting of multiple ag …

Decision Support for Product Development: Using Computational Intelligence for Information Acquisition in Enterprise Databases
M Relich – 2020 – books.google.com
Page 1. Computational Intelligence Methods and Applications Marcin Relich Decision Support for Product Development Using Computational Intelligence for Information Acquisition in Enterprise Databases Page 2. Computational …

Adaptable Automation with Modular Deep Reinforcement Learning and Policy Transfer
Z Raziei, M Moghaddam – arXiv preprint arXiv:2012.01934, 2020 – arxiv.org
Page 1. Adaptable Automation with Modular Deep Reinforcement Learning and Policy Transfer Zohreh Raziei, Mohsen Moghaddam? Department of Mechanical and Industrial Engineering, Northeastern University, Boston, MA 02115, United States Abstract …

Self-adaptive mussels wandering optimization algorithm with application for artificial neural network training
AA Abusnaina, R Abdullah, A Kattan – Journal of Intelligent Systems, 2020 – degruyter.com
De Gruyter De Gruyter …

Decision Support for Product Development
M Relich – Springer
Page 1. Computational Intelligence Methods and Applications Marcin Relich Decision Support for Product Development Using Computational Intelligence for Information Acquisition in Enterprise Databases Page 2. Computational Intelligence Methods and Applications …

Spectral graph-based features for recognition of handwritten characters: a case study on handwritten Devanagari numerals
MI Bhat, B Sharada – Journal of Intelligent Systems, 2020 – degruyter.com
De Gruyter De Gruyter …

Fractional Fuzzy Clustering and Particle Whale Optimization-Based MapReduce Framework for Big Data Clustering
O Kulkarni, S Jena, CH Sanjay – Journal of Intelligent Systems, 2020 – degruyter.com
De Gruyter De Gruyter …

Symbolic Learning and Reasoning With Noisy Data for Probabilistic Anchoring
P Zuidberg Dos Martires, N Kumar… – Frontiers in Robotics …, 2020 – lirias.kuleuven.be
… Some notable refinements include the integration of conceptual spaces (Chella et al., 2003, 2004), the addition of bottom-up anchoring (Loutfi et al., 2005), extensions for multi-agent systems (LeBlanc and Saffiotti, 2008), considerations for non-traditional sensing modalities and …

Exploiting the semantic web for the automatic extraction of Los Angeles city data
M BUCCHI – 2020 – politesi.polimi.it
Page 1. POLITECNICO DI MILANO Management Engineering Course Study On Digital Business And Market Innovation Master Thesis Exploiting the Semantic Web for the Automatic Extraction of Los Angeles City Data ADVISOR: Prof. Letizia Tanca CO-ADVISOR: Prof …

Formal Verification-based Design Model Repair
C Cai – 2020 – researchspace.auckland.ac.nz
… Residual Network (ResNet). A ResNet is constructed by stacking a number of residual building blocks together. Restricted Probabilistic Model Fulfilment (RPMF). RPMF is a reachability repair algorithm that enables B models to achieve given goal states. Semantic Learning …

Graded Soft Expert Set as a Generalization of Hesitant Fuzzy Set
A Qayyum, T Shaheen – Journal of Intelligent Systems, 2020 – degruyter.com
De Gruyter De Gruyter …

A History and Theory of Textual Event Detection and Recognition
Y Chen, Z Ding, Q Zheng, Y Qin, R Huang… – IEEE Access, 2020 – ieeexplore.ieee.org
… Mining interesting knowledge from this textual data is a challenging task because it consists of unstructured or semistructured text that are written in natural language … The query can be structured (eg, regular expression) or unstructured (eg, noun phrase or natural language) …

Understanding the Application and Benefits of Learning-based Methods in Nuclear Science and Engineering
ME Gómez Fernández – 2020 – ir.library.oregonstate.edu
Page 1. Page 2. AN ABSTRACT OF THE DISSERTATION OF Mario Enrique Gómez Fernández for the degree of Doctor of Philosophy in Radiation Health Physics presented on June 1, 2020. Title: Understanding the Application and Benefits of Learning-based Methods in …

Representations for intelligent navigation in unfamiliar environments
GJ Stein – 2020 – dspace.mit.edu
… The learned vertex-edge sensor is noisy, yet via introduction of a probabilistic model, the agent can identify erroneous detections of … monocular images (Chapter 5). • A mapping formulation and accompanying probabilistic model that allows for …

Connected Vehicles in the Internet of Things
Z Mahmood – 2020 – Springer
… With the goal of improving the quality and usability of computer technologies, topics include global software development, multi-agent systems, public administration platforms, socio-economic factors and user-centric design. ISBN: 9781466664852 …

A review of algorithms and techniques for image-based recognition and inference in mobile robotic systems
TAQ Tawiah – International Journal of Advanced Robotic …, 2020 – journals.sagepub.com
Autonomous vehicles include driverless, self-driving and robotic cars, and other platforms capable of sensing and interacting with its environment and navigating without human help. On the other ha…

Artificial Intelligence in Criminal Justice Settings:: Where should be the limits of Artificial Intelligence in legal decision-making? Should an AI device make a decision …
O Cibrian Egido – 2020 – addi.ehu.es
… certain domains at the level of human experts (eg Deep Blue) (Taulli, 2019); 6. Natural Language Processing (NLP). Field intended to make computer systems … They are large-margin estimation methods used for probabilistic models. It is halfway between parametric and …

Reinforcement learning with limited prior knowledge in long-term environments
D Bossens – 2020 – eprints.soton.ac.uk
… Around the same time, reinforcement learning was formalised in the dynamic programming of Bellman [19] where a probabilistic model of state … allowed impressive perfor- mance on tasks difficult for other AI techniques, such as image recognition and natural language processing …

Machine Learning for Advanced Wireless Sensor Networks: A Review
T Kim, LF Vecchietti, K Choi, S Lee… – IEEE Sensors …, 2020 – ieeexplore.ieee.org
… expressions. The DL technique that has attracted increased attention lately due to achieving breakthrough results in important areas such as natural language processing, image classification [64], Page 2. 1530-437X (c) 2020 IEEE …

A review on reinforcement learning: Introduction and applications in industrial process control
R Nian, J Liu, B Huang – Computers & Chemical Engineering, 2020 – Elsevier
… Rapid advancements in computer hardware and ever-cheapening data storage combined with AI’s ability to ‘self-learn’ has pushed AI to become the forefront algorithm for many applications such as computer vision and natural language processing …

AI in Finance: A Review
L Cao – Available at SSRN 3647625, 2020 – papers.ssrn.com
… science, data analytics, knowledge discovery, computer vision, sig- nal processing, image processing, natural language processing (NLP … risk analytics, probabilistic model- ing, classification, clustering, semi- supervised learning, behavior model- ing, sequential modeling, event …

Governance of Artificial Intelligence in Finance
L Dupont, O Fliche, S Yang – Banque De France, 2020 – acpr.banque-france.fr
… post-processing may have a significant impact as well, such as in the case of methods aiming to remove or reduce discriminatory biases4 from already trained models – for example by cancelling out the dependency of predictions made by a probabilistic model on sensitive …

Framework for application of machine learning algorithms in telecommunications
J Nieminen – 2020 – aaltodoc.aalto.fi
… [2] • Machine learning has shown promise in many fields, for example natural language processing, and neural networks excel at finding patterns that can be exploited in receiver design. For example, some approaches are detailed in the paper by Wang et al …

Adaptive Guidance for Online Learning Environments
J Bassen – 2020 – search.proquest.com
Page 1. ADAPTIVE GUIDANCE FOR ONLINE LEARNING ENVIRONMENTS A DISSERTATION SUBMITTED TO THE DEPARTMENT OF COMPUTER SCIENCE AND THE COMMITTEE ON GRADUATE STUDIES OF STANFORD UNIVERSITY …