Probabilistic Models, Multi-agent Systems & Natural Language 2017


Notes:

The vector space and probabilistic models are the two major examples of the statistical retrieval approach. Both models use statistical information in the form of term frequencies to determine the relevance of documents with respect to a query. Probabilistic models usually attempt to determine the relationship between a document and a query through a set of terms that are considered as features.

  • Data-driven medicine
  • Natural language processing models

Resources:

Wikipedia:

References:

See also:

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


Intelligent control systems
SN Vassilyev, AY Kelina, YI Kudinov… – Procedia Computer …, 2017 – Elsevier
… a conflict environment, • the use of the determininistic and probabilistic models for description … scale, and at the level of group interaction of decentralized multi-agent systems … and knowledge processing, • operating with partially formalized and natural language texts, • abductive …

On predicting learning styles in conversational intelligent tutoring systems using fuzzy decision trees
K Crockett, A Latham, N Whitton – International Journal of Human …, 2017 – Elsevier
… OSCAR-CITS is a sophisticated multi-agent system that aims to imitate a human tutor by … By modelling a classroom tutorial style and engaging in a natural language dialogue, OSCAR … Bayesian networks are probabilistic models that have been used to model the relationships …

Variational inference: A review for statisticians
DM Blei, A Kucukelbir, JD McAuliffe – Journal of the American …, 2017 – Taylor & Francis
… precise inferences. We might use variational inference when fitting a probabilistic model of text to one billion text documents and where the inferences will be used to serve search results to a large population of users. In this …

Combining devs and model-checking: Concepts and tools for integrating simulation and analysis
BP Zeigler, JJ Nutaro, C Seo – International Journal of …, 2017 – inderscienceonline.com
… Finally, cooperative multi-agent systems raise the state space explosion exponentially through the cross product of … C. Another example is the modelling language used by the probabilistic model checker PRISM … et al., 2007) which is a foundation of DEVS Natural Language (DNL …

Methodologies for realizing natural-language-facilitated human-robot cooperation: A review
R Liu, X Zhang – arXiv preprint arXiv:1701.08756, 2017 – arxiv.org
… Fig. 1. Promising areas using natural-language-based HRC. (a) is daily robotic assistance using NL[32] … Probabilistic model recommends human-unmentioned knowledge for a robot according to the probabilistic correlations …

From Formalised State Machines to Implementations of Robotic Controllers
W Li, A Miyazawa, P Ribeiro, A Cavalcanti… – arXiv preprint arXiv …, 2017 – arxiv.org
… In these works, finite state-machine controllers were de- scribed using natural language, and there was no direct mapping from the high-level specification to … Exploiting uml in the design of multi-agent systems … Analysing robot swarm behaviour via probabilistic model checking …

Detecting and predicting the topic change of Knowledge-based Systems: A topic-based bibliometric analysis from 1991 to 2016
Y Zhang, H Chen, J Lu, G Zhang – Knowledge-Based Systems, 2017 – Elsevier
… Step, Description, #Term. 0, Natural language processing – to retrieve raw terms from abstract and title, 49,780 … 23, T07-pRec, pattern recognition, discriminant analysis, discriminative, dimensionality. 24, T24-maSys, multi agent system, trajectory, quality of service, trustworthiness …

Choosing the Optimal Segmentation Level for POS Tagging of the Quranic Arabic
FM Ba-Alwi, M Albared… – British Journal of Applied …, 2017 – journalrepository.org
… The choice of the segmentation level or the input unit, word-based or morpheme-based, is a major issue in designing any Arabic natural language processing system … Keywords: Arabic natural language processing; POS tagging; segmentation levels. 1. INTRODUCTION …

Empirical methods for modelling persuadees in dialogical argumentation
A Hunter, S Polberg – Proceedings of the International Conference on …, 2017 – cs.ucl.ac.uk
… We assume the system cannot understand arguments presented in natural language, given the complexity of processing arguments in free text … A probabilistic model of the opponent has been used in a strategy allowing the selection of moves based on what it believes the other …

Coordinating Distributed Speaking Objects
M Lippi, M Mamei, S Mariani… – … Systems (ICDCS), 2017 …, 2017 – ieeexplore.ieee.org
… not be interpreted solely as the capability of interact- ing via natural language (which nevertheless is an … solutions to these tasks, by merging first-order logic with probabilistic models and statistical … The research field of learning in multi-agent systems has a long history in artificial …

17 Distributed Data and Information Fusion in Visual Sensor Networks
F Castanedo, J Gomez-Romero… – … Data Fusion for …, 2017 – books.google.com
… reasoning problem, in which case it is tackled through probabilistic models (Markov models … To the speech act theory, spoken sentences in natural language are actions that produce … The current standards for communication in multi-agent systems are defined in the Foundation …

Multi-agent System for Privacy Protection Through User Emotions in Social Networks
G Aguado, V Julian, A Garcia-Fornes – … of Agents and Multi-Agent Systems, 2017 – Springer
… Diao et al. [23] introduced a probabilistic model that used … Open image in new window. Fig. 1. Arquitecture of the multi-agent system. 3.2 Main Components (Agents) of the System … In: Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing …

Machine Learning & Knowledge Extraction (MAKE) for Health Informatics: Towards educating a new kind of graduates
A Holzinger – pdfs.semanticscholar.org
… framework PyMC3[15], which allows automatic Bayesian inference on user-defined probabilistic models … Tutorial 03: Machine Learning from Text focuses on natural language understanding and … Module 12: Discrete Multi-Agent Systems on the topic of stochastic simulation of …

Researcher profiling: Finding representative phrases for researchers
K Zhou – 2017 – ideals.illinois.edu
… natural language; multi agent system; artificial intelligence; … logic program; natural language; finite state … visual recognition, spatial temporal, event detection, semi supervise, probabilistic model, visual model, supervise segmentation …

Assertional Logic: Towards an Extensible Knowledge Model
Y Zhou – arXiv preprint arXiv:1701.03322, 2017 – arxiv.org
… also highly influential to many other subfields in AI, including expert systems, multi-agent systems, planning, uncer … have been developed, and important applications have been found in machine learning, natural language pro- cessing … Probabilistic Models with Unknown Objects …

A Robust Algorithm: Find an Unknown Person via Referring Grounding
X Wang, F Wu, D Lu, X Chen – robocup2017.org
… Multi-Agent Systems Lab, School of Computer Science and Technology, University of Science and Technology … simple but robust method to recognize an un- known person described in natural language … and perceptu- al data are correct, we use a probabilistic model to ground …

A multi-agent approach to adaptive learning using a structured ontology classification system
KE Ehimwenma – 2017 – shura.shu.ac.uk
Page 1. A multi-agent approach to adaptive learning using a structured ontology classification system EHIMWENMA, Kennedy Efosa Available from Sheffield Hallam University Research Archive (SHURA) at: http://shura.shu.ac.uk/18747 …

Determination of Distant Learner’s Sociological Profile Based on Fuzzy Logic and Naïve Bayes Techniques
Y Chaabi, L Khadija, F Jebbor… – International Journal of …, 2017 – journals.sfu.ca
… The existing system, described in [4, 21], is based on multi-agent systems (Fig- ure.2 … The bag-of-words model is a simplifying representation used in natural language processing and … We must looB at four probabilistic models of messages, each of them represent messages as …

Management of Multimodal User Interaction in Companion-Systems
F Schüssel, F Honold, N Bubalo, M Weber… – Companion …, 2017 – Springer
… Another interesting approach is presented in [19]. The authors present a multi-agent system, where past interactions are taken into account to reason about the new output. They recommend a machine learning approach for case-based reasoning …

Multi-objective policy generation for mobile robots under probabilistic time-bounded guarantees
B Lacerda, D Parker, NA Hawes – 2017 – ora.ox.ac.uk
… The natural language description of the primary task of water delivery is reasonably … In particular we use multi-objective probabilistic model checking, to generate policies that cap- ture the trade-off between timely task completion and gath- ering of secondary task reward …

A Hybrid Architecture for Multi-Party Conversational Systems
MG de Bayser, P Cavalin, R Souza, A Braz… – arXiv preprint arXiv …, 2017 – arxiv.org
… A definition that mixes both concepts herein present is: A chatbot is an agent that interacts through natural language … Bohus and Horowitz [20] have proposed a computational probabilistic model for speech-based systems, but we are not … (ii) Coordination of Multi-Agent Systems …

An Approach to Language Modelling for Intelligent Document Retrieval System
A Kamma – 2017 – diva-portal.org
… 3.3.2 Probabilistic Model……………16 … The main requirements of these systems are, firstly the user should be able to enter the natural language like words, phrases and sentences etc., without the use of operators …

M Tech in Computer Science and Engineering (Software Engineering & Intelligent Systems) Semester I Sr. No. Course Code
CC Hours – COURSES OF STUDY FOR POST GRADUATE … – 14.139.111.180
… CE610 Information Retrieval Systems Syllabus: Introduction: Basic Concepts, Retrieval Process Modeling–A Formal Characterization of IR Models, Classic Information Retrieval (Boolean model, Vector Model, Probabilistic Model), Alterative Set Theoretic Models, Alternative …

Recommendation of Songs in Music Streaming Services: Dealing with Sparsity and Gray Sheep Problems
D Sánchez-Moreno, ABG González… – … and Multi-Agent Systems, 2017 – Springer
… PAAMS 2017: Trends in Cyber-Physical Multi-Agent Systems … an information based measure and its application to problems of ambiguity in natural language … T., Okuno, HG: Hybrid collaborative and content-based music recommendation using probabilistic model with latent …

State-of-the-Art and Open Challenges in RTS Game-AI and Starcraft
K Adil, F Jiang, S Liu, W Jifara, Z Tian, Y Fu – researchgate.net
… The problem of learning probabilistic models of high-level strategic behavior in the real-time strategy game Starcraft is … as this work is partially funded by the MOE–Microsoft Key Laboratory of Natural Language Processing and … [15] Ferber, J., “Multi-agent systems: an introduction …

AppLP: A Dialogue on Applications of Logic Programming
DS Warren, YA Liu – arXiv preprint arXiv:1704.02375, 2017 – arxiv.org
… may help); and program derivation, for generating a program from a natural language specification of … for probabilistic model checking, just as it was for non-probabilistic model checking … expressive languages, such as pi-calculus, mobile ad-hoc networks, multi-agent systems, etc …

Towards a framework for computational persuasion with applications in behaviour change
A Hunter – Argument & Computation – content.iospress.com
… development of software solvers for determining extensions (see for example [33,137]), and the application of natural language processing techniques … Probabilistic models of the opponent have been used in some strategies allowing the selection of moves for an agent based …

Towards Argumentation-based Recommendations for Personalised Patient Empowerment
JM Fernández, F Miralles, A Steblin… – Second …, 2017 – pdfs.semanticscholar.org
… ing systems and tools; • Computing methodologies ? Discourse, dialogue and pragmatics; Multi-agent systems; … to, for instance, gen- erate explanation sentences through Natural Language Processing (NLP … of solutions, since it merges logic with probabilistic models to detect …

Spatial Referring Expression Generation for HRI: Algorithms and Evaluation Framework
L Kunze, T Williams, N Hawes, M Scheutz – 2017 – pdfs.semanticscholar.org
… REG. 1 Introduction Many tasks in Human-Robot Interaction (HRI) require robots to use natural language (NL) to refer to objects, places, or people in their environment, a task known as Referring Ex- pression Generation (REG) …

Analysis and Modeling of 3D Indoor Scenes
R Ma – arXiv preprint arXiv:1706.09577, 2017 – arxiv.org
… be modeled. Natural language is arguably the most accessible input for content creation. Generating 3D scenes from text has been a long and on-going pursuit since the pioneering work on WordsEye [13]. WordsEye, along …

A brief introduction to weakly supervised learning
ZH Zhou – National Science Review, 2017 – academic.oup.com
Abstract. Supervised learning techniques construct predictive models by learning from a large number of training examples, where each training example has a la.

Artificial intelligence and business: A hybrid genetic algorithm for e-business strategic planning and performance evaluation
AD Lipitakis, EAEC Lipitakis – The Business & Management …, 2017 – search.proquest.com
… financial trading, healthcare, marketing personalization, recommendations, natural language processing, online … systems, evolution of co-operation and communication in multi-agent systems) … optimization by building and using probabilistic models, Computational optimization …

Planning for persuasion
E Black, AJ Coles, C Hampson – Proceedings of the 16th Conference on …, 2017 – dl.acm.org
… All rights reserved. can use against it. Recent works have considered how the propo- nent might use an uncertain (probabilistic) model of its opponent in order to guide its choice of which arguments to assert (eg, [4, 18, 22, 24, 25, 26, 36, 39]) …

A glass-box interactive machine learning approach for solving NP-hard problems with the human-in-the-loop
A Holzinger, M Plass, K Holzinger, GC Crisan… – arXiv preprint arXiv …, 2017 – arxiv.org
… to a hypothesis space H = {H1,H2, …, Hn}, and a probabilistic model relating each … have enormous problems when lacking contextual information, eg in natural language translation/curation … The artificial ant colonies are multi-agent systems that work on problems represented by …

Intelligent information processing for building university knowledge base
J Koperwas, ? Skonieczny, M Koz?owski… – Journal of Intelligent …, 2017 – Springer
… The module has been implemented as a multi-agent system. As depicted in Fig … For a few years, both Wikipedia and DBpedia have been used in many areas concerned with natural language processing, in particular for information retrieval and information extraction …

Day Workshop Towards Intelligent Social Robots: Social Cognitive Systems in Smart Environments
A Aly, S Griffiths, V Nitsch, T Taniguchi, S Wermter… – 2017 – researchgate.net
… Similarly, the fields of IR, normative multi-agent systems [17] and computational organization theory [18] Page 5. operate on diverse definitions. Even within the field of IR, institutions are modeled dissimilarly among different research groups …

A Thematic Study of Requirements Modeling and Analysis for Self-Adaptive Systems
Z Yang, Z Li, Z Jin – arXiv preprint arXiv:1704.00420, 2017 – arxiv.org
… Verifying requirements with probabilistic models DTMC & PCTL [S95, S96, S97] 3 … Trops4AS [S55] to deal with the re- quirements modeling of self-organizing multi-agent systems … RELAX specifications are structured with lots of natural language and Boolean operators, such as …

Assistive and Adaptive Dialog Management
F Nielsen, W Minker – Companion Technology, 2017 – Springer
… requires complex and elaborate models, and tends to get unsolvable fast, only the augmentation process is controlled by a probabilistic model … Hence, it is translated by the explanation manager using template-based natural language generation into human-readable text …

Verbalization of Service Robot Experience as Explanations in Language Including Vision-Based Learned Elements
SPP Selvaraj – 2017 – pdfs.semanticscholar.org
… Our initial introduction of verbalization requires manual grounding of the log data to natural language phrases which makes the algorithm unscalable … We then discuss and an- alyze the classifier we use to ground the log data to natural language automatically …

Probabilistic reasoning with abstract argumentation frameworks
A Hunter, M Thimm – Journal of Artificial Intelligence Research, 2017 – jair.org
… medicine as just water, then we will have high belief in argument A and low belief in argument B (eg P(A)=0.9 and P(B) = 0), leading to an epistemic extension containing just A. In practice, we can make these judgments when hearing arguments presented in natural language …

The Rise of Cognitive Science in the 20th Century
C Figdor – philpapers.org
… No wonder, then, that Turing’s model was immediately elaborated at a level appropriate to human-centered psychology: the symbols were interpreted as natural- language-like concepts or mental representations, and the rules were the rules of deductive logic or heuristics …

Modal Cognitivism and Modal Expressivism
H Khudairi – philpapers.org
… Baltag (2003) develops a colagebraic semantics for dynamic-epistemic logic, where coalgebraic functors are intended to record the informational dynamics of single- and multi- agent systems … to the remit of natural language semantics – is limited to substitutional quan …

Reasoning in non-probabilistic uncertainty: Logic programming and neural-symbolic computing as examples
TR Besold, AA Garcez, K Stenning, L van der Torre… – Minds and …, 2017 – Springer
… But it has the important consequence, already mentioned, that—like natural language conditionals—LP … it should be noted that LP has some close correspondences with probabilistic models … serve as mechanisms to effectively deal with coordination in multi-agent systems (MAS …

A review of spatial reasoning and interaction for real-world robotics
C Landsiedel, V Rieser, M Walter, D Wollherr – Advanced Robotics, 2017 – Taylor & Francis
… 2. Natural language human–robot interaction about space. One of the most direct and natural ways to communicate with robots is natural language. In order for … 2.2. Interpreting spatial natural language. Natural language provides …

Smart Environments: What is it and Why Should We Care?
D Wolter, A Kirsch – KI-Künstliche Intelligenz, 2017 – Springer
… AI research that advanced from single-computer intelligent to networked multi-agent systems and is … 15, for example], all the way to more implicit natural language instructions and … unknown values and their complexity inhibits the development of reliable (probabilistic) models [16 …

A probabilistic formalization of the appraisal for the OCC event-based emotions
J Gluz, PA Jaques – Journal of Artificial Intelligence Research, 2017 – jair.org
… Examples of those agents are embodied conversational agents, which are personified characters that interact with users in natural language (Cas- sell, 2000), and agents representing non-player characters in popular role-playing games (Sindlar et al., 2009) …

Distributed Learning in Referral Networks
AR KhudaBukhsh – 2017 – cs.cmu.edu
… In presence of annotator disagreements, Learning from crowd, pro- posed in [38, 50], presents a probabilistic model to model the labeling process and a subsequent Expectation-Maximum (EM) step is used to obtain maximum likelihood estimates (MLEs) of un- observed …

Social eye gaze in human-robot interaction: a review
H Admoni, B Scassellati – Journal of Human-Robot Interaction, 2017 – dl.acm.org
Page 1. Social Eye Gaze in Human-Robot Interaction: A Review Henny Admoni and Brian Scassellati Department of Computer Science, Yale University This article reviews the state of the art in social eye gaze for human-robot interaction (HRI) …

Reasoning in Non-Probabilistic Uncertainty?
TR Besold, AA Garcez… – arXiv preprint arXiv …, 2017 – pdfs.semanticscholar.org
… [2009] argue that peoples’ judgements of likelihoods in uncertainty do not obey probabilistic models … But it has the important consequence, already mentioned, that— like natural language conditionals—LP conditionals do not iterate, especially in the antecedent, to produce …

Commonsense Knowledge for 3D Modeling: A Machine Learning Approach
K Hassani – 2017 – ruor.uottawa.ca
… signals within a scene description in natural language; (2) grounding spatial relations to automatically position … of spatial signals within a scene description in natural language; (2) grounding spatial relations to automatically …

Creating Affective Autonomous Characters Using Planning in Partially Observable Stochastic Domains
X Huang, S Zhang, Y Shang… – IEEE Transactions on …, 2017 – ieeexplore.ieee.org
Page 1. 42 IEEE TRANSACTIONS ON COMPUTATIONAL INTELLIGENCE AND AI IN GAMES, VOL. 9, NO. 1, MARCH 2017 Creating Affective Autonomous Characters Using Planning in Partially Observable Stochastic Domains …

Experiment and Evaluation in Information Retrieval Models
K Latha – 2017 – books.google.com
… Page 9. 4.4 Probabilistic Models 4.4.1 Probabilistic Ranking Principle (PRP) 4.4.2 Binary Independence Retrieval (BIR) Model 4.4.3 The Probabilistic Indexing Model 4.5 Language Model 4.5.1 Multinomial Distributions Model 4.5.2 The Query Likelihood Model 4.5.3 Extended …

A User Perception–Based Approach to Create Smiling Embodied Conversational Agents
M Ochs, C Pelachaud, G Mckeown – ACM Transactions on Interactive …, 2017 – dl.acm.org
… As a second step, we propose a probabilistic model to automatically compute the user’s potential perception of the embodied conversational agent’s social stance depending on its smiling behavior and on its physical appearance …

Social collaborative filtering by trust
B Yang, Y Lei, J Liu, W Li – IEEE transactions on pattern …, 2017 – ieeexplore.ieee.org
… 3.1 Probabilistic Models of Truster and Trustee In social collaborative filtering by trust, we have a rating matrix R ¼ ½Rij mÂn, a trust matrix T ¼ ½Tik mÂm, a user fea- ture matrix U 2 RdÂm, an item feature matrix V 2 RdÂn, a truster feature matrix B 2 RdÂm, and a trustee feature …

Elasticity in cloud computing: state of the art and research challenges
Y Al-Dhuraibi, F Paraiso, N Djarallah… – IEEE Transactions on …, 2017 – ieeexplore.ieee.org
… Model solving mechanisms are approaches based on probabilistic model checking or mathematical mod- eling frameworks to study the diverse behaviours of the system and anticipates its future states such as Markov Decision Processes (MDPs), probabilistic timed automata …

Perspectives on research in artificial intelligence and artificial general intelligence relevant to DoD
R Potember – 2017 – dtic.mil
… training with much smaller data sets; and other kinds of probabilistic models such as … list of the sub-fields of AI might be: computer vision, natural language processing, robotics (including human-robot interactions), search and planning, multi-agent systems, social media …

3.28 Qualitative and Multi-Attribute Learning from Diverse Data Collections
M Ben-Chen, F Chazal, LJ Guibas… – … in Geometric Data, 2017 – drops.dagstuhl.de
Page 19. Mirela Ben-Chen, Frédéric Chazal, Leonidas J. Guibas, and Maks Ovsjanikov 17 3.28 Qualitative and Multi-Attribute Learning from Diverse Data Collections Hao Zhang (Simon Fraser University–Burnaby, CA) License …

Advances in Artificial Intelligence: From Theory to Practice: 30th International Conference on Industrial Engineering and Other Applications of Applied …
S Benferhat, K Tabia, M Ali – 2017 – books.google.com
… Yootthapong Tongpaeng Uncertainty Management A Robust, Distributed Task Allocation Algorithm for Time-Critical, Multi Agent Systems Operating in … Antonis C. Kakas dARe – Using Argumentation to Explain Conclusions from a Controlled Natural Language Knowledge Base …

Argumentation mining in user-generated web discourse
I Habernal, I Gurevych – Computational Linguistics, 2017 – MIT Press
… (2014). Second, not all related works are tightly connected to argumentation theories, resulting in a gap between the substantial research in argumentation itself and its adaptation in natural language processing (NLP) applications …

Model-driven development and verification of fault tolerant systems
K Javed – 2017 – doria.fi
Page 1. Turku Centre for Computer Science TUCS Dissertations No 223, May 2017 Kashif Javed Model-Driven Development and Verification of Fault Tolerant Systems Page 2. Page 3. Model-Driven Development and Verification of Fault-Tolerant Systems Kashif Javed …

Advances in Soft Computing: 15th Mexican International Conference on Artificial Intelligence, MICAI 2016, Cancún, Mexico, October 23–28, 2016 …
O Pichardo-Lagunas, S Miranda-Jiménez – 2017 – books.google.com
… Instituto Tecnológico de Cancún, Mexico Area Chairs Natural Language Processing Grigori … de Guanajuato, Mexico Logic, Knowledge-Based Systems, Multi-agent Systems and Distributed AI … Jose Raymundo Marcial Romero Fuzzy Systems and Probabilistic Models in Decision …

Measuring the radicalisation risk in social networks
R Lara-Cabrera, AG Pardo, K Benouaret, N Faci… – IEEE …, 2017 – ieeexplore.ieee.org
… Where the different elements are evaluated by a probabilistic model in order to measure their membership to the different communities … Our proposal uses features from diverse research field such as Natural Language Processing, Data Mining and Statistics …

A Learning Based Optimal Human Robot Collaboration with Linear Temporal Logic Constraints
B Wu, B Hu, H Lin – arXiv preprint arXiv:1706.00007, 2017 – arxiv.org
… logic constraints (LTL) [8], a rich and expressive specification language to specify desired properties that’s close to human natural language … the optimal control policy subject to LTL specifications and optimizing the weighted average cost function on a non- probabilistic model …

An On-line Truthful and Individually Rational Pricing Mechanism for Ride-sharing
M Asghari, C Shahabi – 2017 – pdfs.semanticscholar.org
… An LDA is a generative probabilistic model for collections of discrete data, in which each item of a collection is modeled as a finite mixture … as an infinite mixture over an underlying set of topic probabilities[4]. For example LDA is widely used in natural language processing where …

Human societies: Understanding observed social phenomena
B Edmonds, P Lucas, J Rouchier, R Taylor – Simulating Social Complexity, 2017 – Springer
… the gap between essentially formal symbols with precise but limited meaning and the rich semantic associations of the observed social world (eg as expressed in natural language) is particularly … The authors develop and parameterise a probabilistic model of team selection …

Neural-Symbolic Learning and Reasoning: A Survey and Interpretation
TR Besold, AA Garcez, S Bader, H Bowman… – arXiv preprint arXiv …, 2017 – arxiv.org
… Here, successfully addressed application scenarios include business process modelling, service-oriented computing (trust management and fraud prevention in e-commerce), syn- chronisation and coordination in large multi-agent systems, and multimodal processing and …

Logical Formulizations of Commonsense Reasoning: A Survey
E Davis – Journal of Artificial Intelligence Research, 2017 – jair.org
… Natural language processing. Resolving ambiguities in natural language text and ut- terances is a matter of finding the most plausible interpretation; and determining the … This excludes representations like natural language with its intricate syntactic and semantic rules …

Event Extraction and Temporal Ordering towards Narrative Model Generation
W James – 2017 – pdfs.semanticscholar.org
… 7.5 Significance . . . . . 42 1 Introduction Natural Language Processing (NLP) has had significant progress in the last decade … An unsupervised probabilistic model called Resolver is then used to link extractions that indicate the same relation …

The Fundamentals of Computational Intelligence: System Approach
MZ Zgurovsky, YP Zaychenko – 2017 – Springer
… the search for solutions, the pattern recognition systems, machine translation, machine learning, action planning, agents and multi-agent systems, self-organization and … 6. the ability to self-organization and self-development; 7. the ability to understand natural language texts; 8 …

Situation Understanding for Turn-Taking in Human-Robot Dialogue
???? – 2017 – ir.library.osaka-u.ac.jp
… 5 Page 21. 4?Natural Language Understanding 5. Dialogue Management 6. Natural Language Generation 7. Text-to-speech Synthesis … Hatice et al. [31] developed a humanoid robot Kaspar and used probabilistic models for natural turn-taking in drumming interaction games …

” I can assure you [$\ldots $] that it’s going to be all right”–A definition, case for, and survey of algorithmic assurances in human-autonomy trust relationships
BW Israelsen – arXiv preprint arXiv:1708.00495, 2017 – arxiv.org
… For communicating with humans this could involve some type of natural language interface … Trust is critical in interpersonal relationships, and it a ects the dynamics of intelligent multi-agent systems as simple as one-on-one personal interactions [74], to more complicated ones …

Autonomous Agents Modelling Other Agents: A Comprehensive Survey and Open Problems
SV Albrecht, P Stone – arXiv preprint arXiv:1709.08071, 2017 – arxiv.org
Page 1. Autonomous Agents Modelling Other Agents: A Comprehensive Survey and Open Problems Stefano V. Albrechta, Peter Stoneb aThe University of Edinburgh, United Kingdom bThe University of Texas at Austin, United States Abstract …

Topic Flow in Social Media Conversations
CA Crawford – 2017 – search.proquest.com
… Topic flow is how topics evolve from parent to reply document. We propose three different probabilistic models for determining topic flow … Topic ow is how topics evolve from. parent to reply document. We propose three dierent probabilistic models for determining topic ow. Two of …

On the relation between the general affective meaning and the basic sublexical, lexical, and inter-lexical features of poetic texts—a case study using 57 …
S Ullrich, A Aryani, M Kraxenberger, AM Jacobs… – Frontiers in …, 2017 – frontiersin.org
The literary genre of poetry is inherently related to the expression and elicitation of emotion via both content and form. To explore the nature of this affective impact at an extremely basic textual level, we collected ratings on eight different general affective meaning scales—valence …

” Dave… I can assure you… that it’s going to be all right…”–A definition, case for, and survey of algorithmic assurances in human-autonomy trust relationships
BW Israelsen, NR Ahmed – arXiv preprint arXiv:1711.03846, 2017 – arxiv.org
… For communicating with humans this could involve some type of natural language interface … Trust is critical in interpersonal relationships, and it a ects the dynamics of intelligent multi-agent systems as simple as one-on-one personal interactions [79], to more complicated ones …

Historical overview of formal argumentation
H Prakken – IfCoLog Journal of Logics and their Applications, 2017 – dspace.library.uu.nl
Page 1. Historical Overview of Formal Argumentation Henry Prakken Department of Information and Computing Sciences, Utrecht University, The Netherlands Faculty of Law, University of Groningen, The Netherlands h.prakken@uu.nl …

Event-based automated refereeing for robot soccer
D Zhu, M Veloso – Autonomous Robots, 2017 – Springer
… according to external input. We formalized the structure of an SSL game by taking the natural-language rules document of the SSL and creating a hybrid automaton that describes the structure of the game. A hybrid automaton …

Ontology-Based Data Access Leveraging Subjective Reports
GI Simari, C Molinaro, MV Martinez, T Lukasiewicz… – 2017 – Springer
… Intensional level: The following are examples of intensional knowledge—we provide them in natural language, as we have not yet specified an ontological language; we discuss again these elements in the language of specific description logics in Example 1.2 …

Information Extraction from TV Series Scripts for Uptake Prediction
J Wang – 2017 – aut.researchgateway.ac.nz
… of movie scripts was conducted by Agarwal, Balasubramanian, Zheng and Dash (2014). Based on NLP (Natural Language Processing) and ML (Machine Learning) techniques, their approach categorises each line into one of these classes: S for scene boundary; …

Advances in Computational Intelligence: 15th Mexican International Conference on Artificial Intelligence, MICAI 2016, Cancún, Mexico, October 23–28, 2016 …
G Sidorov, O Herrera-Alcántara – 2017 – books.google.com
… Instituto Tecnológico de Cancún, Mexico Area Chairs Natural Language Processing Grigori … de Guanajuato, Mexico Logic, Knowledge-Based Systems, Multi-agent Systems and Distributed AI … Jose Raymundo Marcial Romero Fuzzy Systems and Probabilistic Models in Decision …

Parsing argumentation structures in persuasive essays
C Stab, I Gurevych – Computational Linguistics, 2017 – MIT Press
… in drawing widely accepted conclusions. Computational argumentation is a recent research field in computational linguistics that focuses on the analysis of arguments in natural language texts. Novel methods have broad application …

Explanation in artificial intelligence: Insights from the social sciences
T Miller – arXiv preprint arXiv:1706.07269, 2017 – arxiv.org
… explainer’s 2Note that this does not imply that explanations must be given in natural language, but implies that explanation is a social interaction between the explainer and the explainee. 5 Page 6. beliefs about the explainee’s beliefs …

Design and Analysis of the NIPS 2016 Review Process
NB Shah, B Tabibian, K Muandet, I Guyon… – arXiv preprint arXiv …, 2017 – arxiv.org
Page 1. Design and Analysis of the NIPS 2016 Review Process Nihar B. Shah Machine Learning Department, and Computer Science Department Carnegie Mellon University nihars@cs.cmu.edu Behzad Tabibian Max Planck …

Artificial Intelligence and Games
GN Yannakakis, J Togelius – 2017 – gameaibook.org
… Over the last decade, progress in deep learning has had a profound and transfor- mational effect on many difficult problems, including speech recognition, machine translation, natural language understanding and computer vision …

Clinical decision support: Knowledge representation and uncertainty management
TJM Oliveira – 2017 – repositorium.sdum.uminho.pt
Page 1. Tiago José Martins Oliveira January 2017 UMinho|2017 Clinical Decision Support: Knowledge Representation and Uncertainty Management Universidade do Minho Escola de Engenharia Tiago José Martins Oliveira …

Artificial Intelligence and Games (Second Public Draft)
GN Yannakakis, J Togelius – 2017 – uicvgame.ui.ac.ir
… Deep Blue IBM’s next success story was Watson, a soft- ware system capable of answering questions addressed in natural language … by researchers with AI, optimiza- tion and control background and research experience in adaptive behavior, robotics and multi-agent systems …

Son Doan Trung
OT Recommendation – d-nb.info
… of complex networks, peer-to-peer and on-line social network systems. Since also content aspects shall be considered, a short review on the needed methods of natural language processing will conclude this chapter. Due to …

Semantic Selection of Internet Sources through SWRL Enabled OWL Ontologies
H Almarri – 2017 – westminsterresearch.wmin.ac.uk
… (LLL) Lifelong Learning (MA) Management Agent (MAS) Multi-Agent System (MIS) Management Information Systems (NFL) Non-Formal Learning (NG) Next-generation (NLSE) Natural Language Search Engine (OBA) Online Behavioural Advertising …

Serious Games for Health Rehabilitation
PAC de Sousa Rego – 2017 – repositorio-aberto.up.pt
Page 1. SERIOUS GAMES FOR HEALTH REHABILITATION PAULA ALEXANDRA CARVALHO DE SOUSA REGO TESE DE DOUTORAMENTO APRESENTADA À FACULDADE DE ENGENHARIA DA UNIVERSIDADE DO PORTO EM ENGENHARIA INFORMÁTICA D 2017 …

Haskell Communities and Activities Report
M Maruseac, AS Mena, A Abel, A Granin, H Apfelmus… – 2017 – haskell.org
Index. Haskell Communities and Activities Report. http://tinyurl.com/haskcar. pdf version. Twenty-Seventh Edition – November 2014. Mihai Maruseac, Alejandro Serrano Mena (eds.). Andreas Abel. Alexander Granin. Heinrich Apfelmus. Emil Axelsson. Carl Baatz. Doug Beardsley …

Truth Discovery from Crowdsourced Data
Q Li – 2017 – search.proquest.com
Truth Discovery from Crowdsourced Data. Abstract. Recent years have witnessed an astonishing growth of crowd-contributed data, which has become a powerful information source that covers almost every aspect of our lives …

Graph-based learning and decision making in information networks
C Zhou – 2017 – search.proquest.com
… 2.2 Graphical Models and Exponential Families. 2.2.1 Graphical Model Basics. Graphical models provide a simple way to visualize the structure of a. probabilistic model. In this section, we will give a brief introduction on graphical. models …

Designing a Socially Assistive Robot to Preserve the Dignity of Older Adults
JR Wilson – 2017 – search.proquest.com
Designing a Socially Assistive Robot to Preserve the Dignity of Older Adults. Abstract. The population of older adults worldwide is expected to double between 2025 and 2050, whereas the total population is projected to grow only 34% over the same period …

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