SME (Structure Mapping Engine) 2020


Notes:

Structure mapping engine is an algorithm based on the psychological theory for analogical matching. Analogy can be defined as a comparison of two things. Whereas, metaphor is a thing regarded as representative or symbolic of something else.

Wikipedia:

Reference:

See also:

ATT-Meta ProjectCogSketchComputational Analogy | ThoughtTreasure


Structure-mapping processes enable infants’ learning across domains including language
SJ Hespos, E Anderson, D Gentner – Language and concept acquisition …, 2020 – Springer
… (1999) findings. SEQL and its successor, SAGE, 3 use the structure-mapping engine (SME; Falkenhainer, Forbus, & Gentner, 1989; Forbus et al., 2017) to iteratively compare input examples, creating an ongoing generalization …

Advanced Interoperability Techniques: Structure Mapping Service in CrowdHEALTH Project
SA Lete, C Cavero, A Magdalinou, J Mantas… – Acta Informatica …, 2020 – ncbi.nlm.nih.gov
… In all cases, the Interface Layer handles conversion to and from JavaScript Object Notation (JSON)/ Extensible Markup Language (XML) to one internal format of the structure mapping engine ie JSON. 3.2.2. Knowledge Layer …

Verifying exchange between Aeronautics and Oil&Gas industries through Lateral Thinking
FTGLV Neto, LG Trabasso – Product: Management and …, 2020 – app.periodikos.com.br
… present work purposes to characterize an analogy between the oil well driller and the airplane pilot workstations through the systemic comprehension of human factors, indicating exchange possibilities between them, using the premises on the Structure-Mapping Engine (SME) …

Same/different in visual reasoning
KD Forbus, A Lovett – Current Opinion in Behavioral Sciences, 2021 – Elsevier
… different provide end-points. We then summarize key ideas of structure-mapping theory and the Structure-Mapping Engine, which is used in many of the models below, as well as examine alternatives. We then outline models …

Analogy
C Calì – Glossary of Morphology, 2020 – Springer
… relations. The implementation of the structure-mapping engine requires the recruitment of cognitive functions like working and long-term memory, by which the example and the target are maintained, retrieved, aligned and mapped …

Correction to: The Search for Invariance: Repeated Positive Testing Serves the Goals of Causal Learning
E Lapidow, CM Walker – Language and Concept Acquisition from …, 2020 – books.google.com
… progressive alignment, 92–94 same-different learning, 95 SEQL, 95 SME, 95 social domain, 238–242 structural alignment, 92, 93 teaching trials, 96 vehicles, 225 visual alignment, 96 Structured sequence, 14 Structure-level comparison, 51 Structure-mapping engine (SME), 4 …

Neural analogical matching
M Crouse, C Nakos, I Abdelaziz, K Forbus – arXiv preprint arXiv …, 2020 – arxiv.org
… The representations produced by deep learning techniques are incompatible with off-the-shelf SMT implementations like the Structure-Mapping Engine (SME) [13], while the symbolic graphs that SMT assumes as input are challenging to encode with traditional neural methods …

How do initial ideas evolve into final ones? Exploring the cognitive size, structure and life of ideas using sticky notes
BT Christensen, M Friis-Olivarius – Sticky Creativity, 2020 – Elsevier
… The Structure Mapping Engine (SME) by Forbus, Gentner, and Law (1995) divides the process into four parts: First, blind and local matches between all (typically inconsistent) identical predicates and subpredicates are constructed …

A patient-similarity-based model for diagnostic prediction
Z Jia, X Zeng, H Duan, X Lu, H Li – International journal of medical …, 2020 – Elsevier
… Related studies on analogy reasoning theory in computer science, such as those on the structure-mapping engine [12], ACME [13], the articulation model [14], the NLP-based method [15] and AN-GAN [16], are very impressive but are still unable to be directly used to measure …

Engineering Portfolio
M Rivers – morganrivers.com
… [5] • Works even when multiple changes in variable values occur across scenarios. • Abstracts away insignificant variables. Structure Mapping Engine • Uses maximal mapping, defined as the largest structural mapping. • Engine returns SES (Structural Evaluation Score) …

Visual Relation Detection using Hybrid Analogical Learning
K Chen, KD Forbus – 2021 – aaai.org
… of psychological phenomena. For ex- ample, (Kandaswamy et al., 2014) showed that the Structure Mapping Engine (SME), an analogical matching model, can model learning forced-choice tasks with visual stimuli. Sim- ilarly …

A category theoretic approach to metaphor comprehension: Theory of indeterminate natural transformation
M Fuyama, H Saigo, T Takahashi – Biosystems, 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 …

Mapping natural-language problems to formal-language solutions using structured neural representations
K Chen, Q Huang, H Palangi… – International …, 2020 – proceedings.mlr.press
… (2017) introduced the computational implementation, the Structure Mapping Engine (SME), of the Structure Map- ping Theory. Following these works, Crouse et al. (2018); Chen & Forbus (2018); Chen et al. (2019) applied SME to language and vision problems …

Simulating Infant Visual Learning by Comparison: An Initial Model
K Chen, KD Forbus, D Gentner, SJ Hespos… – 2020 – cognitivesciencesociety.org
… We first describe the component models, then how they are combined. Simulation of analogical processing We use the Structure-Mapping Engine (SME, Forbus et al. (2016)) as a simulation of analogical mapping, and SageWM (Kandaswamy et al …

Not quite any way you slice it: How different analogical constructions affect Raven’s Matrices performance
Y Yang, K McGreggor, M Kunda – … of the Eighth Annual Conference on …, 2020 – par.nsf.gov
… One of the most well-known works is CogSketch plus Structure-Mapping Engine (Falkenhainer et al., 1989; Lovett et al., 2010; Forbus et al., 2011; Lovett & Forbus, 2017), where CogSketch encodes qualitative spatial relations be- tween 2-D objects, and Structure-Mapping …

Corrective Processes in Modeling Reference Resolution
C Nakos, I Rabkina, S Hill, KD Forbus – 2020 – cognitivesciencesociety.org
… The Structure-Mapping Engine (SME; Forbus et al., 2016) is a computational implementation of SMT that has been used to model a wide range of cognitive phenomena, including conceptual change (Friedman & Forbus, 2010), visual similarity (Lovett & Forbus, 2017), and …

Abstraction and Analogy-Making in Artificial Intelligence
M Mitchell – arXiv preprint arXiv:2102.10717, 2021 – arxiv.org
… Early examples include Evans’ geometric-analogy solver,24 Winston’s frame-based system for analogy-making between sto- ries,109 and Falkenhainer et al.’s Structure-Mapping Engine (SME).26 In this section I will describe SME, as well as the Active Symbol Architecture of …

Proactively Suggesting Similar Past Stories Turns “Lessons Learned” Into “Lessons Used”
E Domeshek, D Tuohy, J Ong, D Spangler, T Williams – stottlerhenke.com
… & Kokinov, 2001). The Structure Mapping Engine—an algorithmic implementation of these insights into analogy—has been tested across a range of applications over the course of thirty years (Forbus et al., 2017). In our work …

A connectionist account of the relational shift and context sensitivity in the development of generalisation
PH Thibodeau, A Blonder, SJ Flusberg – Connection Science, 2020 – Taylor & Francis
… Notably, proponents of two modelling approaches that have been at the forefront of the field (Structure Mapping Engine – SME – proposed by Falkenhainer et al., 1989; and Learning and Inference with Schemas and Analogies – LISA – proposed by Hummel & Holyoak, 1997 …

Generating Concepts: Guiding Computational Conceptual Blending with Image Schemas
MM Hedblom – Image Schemas and Concept Invention, 2020 – Springer
… One problem for computational conceptual blending, and related work such as anal- ogy engines (eg Structure Mapping Engine (SME) (Forbus et al., 1989; Gentner, 1983) and Heuristic-Driven Theory Projection (HDPT) (Schmidt et al., 2014)) is the generation of a ‘sensible …

Language and Concept Acquisition from Infancy Through Childhood
JB Childers – Springer
… For example, a simulation using the structure-mapping engine (SME) successfully captures infant learning in the Marcus et al. study of artificial grammar learning. The chapter ends by extending the theory to physical reasoning tasks (covering events) …

Spatial adaptation: modeling a key spatial ability
A Lovett, H Schultheis – Spatial Cognition & Computation, 2020 – Taylor & Francis
… 3.4.1. Implementation. The model uses the Structure-Mapping Engine (SME: Falkenhainer, Forbus & Gentner, 1989) to find the corresponding parts in two objects. Given this information, it can adjust the metric values as in step 2) above and then compare the values …

A Paradigm for Matching Waking Events Into Dream Reports
JX Wang, JY He, T Bin, HY Ma, J Wan, XQ Li… – Frontiers in …, 2020 – frontiersin.org
… concerns. J. Sleep Res. 28:e12697. Google Scholar. Falkenhainer, B., Forbus, KD, and Gentner, D. (1989). The structure-mapping engine: algorithm and examples. Artif. Intellig. 41, 1–63. doi: 10.1016/0004-3702(89)90077-5 …

Spatial alignment facilitates visual comparison.
BJ Matlen, D Gentner, SL Franconeri – Journal of Experimental …, 2020 – psycnet.apa.org
Humans have a uniquely sophisticated ability to see past superficial features and to understand the relational structure of the world around us. This ability often requires that we compare structures, finding commonalities and differences across visual depictions that are arranged …

Effects of Analogical Learning Approaches and Presentation Modalities on Ninth Graders’ Learning Outcome and Eye Movements: a Preliminary Study
SC Chen, HC She – Journal of Science Education and Technology, 2020 – Springer
Page 1. Effects of Analogical Learning Approaches and Presentation Modalities on Ninth Graders’ Learning Outcome and Eye Movements: a Preliminary Study Sheng-Chang Chen1 & Hsiao-Ching She1 © Springer Nature BV 2020 …

A Memory-Augmented Neural Network Model of Abstract Rule Learning
I Sinha, TW Webb, JD Cohen – arXiv preprint arXiv:2012.07172, 2020 – arxiv.org
… [6] and a recent extension of the Structure Mapping Engine [9, 28]. Our goal is somewhat different … Page 13. [9] Falkenhainer, Brian, Forbus, Kenneth D., and Gentner, Dedre. “The Structure-Mapping Engine: Algorithm and Examples”. In: Artificial Intelligence 41.1 (1989), pp …

Comparison and Alignment in Categorization
F Maravilla – 2020 – search.proquest.com
… One factor that makes structure-mapping theory a good candidate is its specific process- level claims. Structure-mapping theory has been formalized in a computational model, the Structure-Mapping Engine (SME) (Falkenhainer et al., 1989). SME functions in a local-to-global …

Preventing inert knowledge: Category status promotes spontaneous structure-based retrieval of prior knowledge.
S Snoddy, KJ Kurtz – Journal of Experimental Psychology: Learning …, 2020 – psycnet.apa.org
… On problem-solving (LS Lees, Trans.). Psychological Monographs, 58(5), i–113. http://dx.doi.org/10.1037/h0093599; Falkenhainer, B., Forbus, KD, Gentner, D. (1989). The structure-mapping engine: Algorithm and examples. Artificial Intelligence, 41, 1-63 …

Word2vec Conjecture and A Limitative Result
FZ Dai – arXiv preprint arXiv:2010.12719, 2020 – arxiv.org
… Computational linguistics, 16(1):22–29. Brian Falkenhainer, Kenneth D. Forbus, and Dedre Gentner. 1989. The structure-mapping engine: Algorithm and examples. Artificial Intelligence, 41(1):1–63. John R Firth. 1957. A synopsis of linguistic theory, 1930-1955 …

Cross-domain Correspondences for Explainable Recommendations.
A Stockdill, D Raggi, M Jamnik, GG Garcia… – ExSS-ATEC …, 2020 – ceur-ws.org
… 2005. Elements of Information Theory. John Wiley & Sons, Ltd, Hoboken, NJ, USA. [4] Brian Falkenhainer, Kenneth D. Forbus, and Dedre Gentner. 1989. The structure- mapping engine: Algorithm and examples. Artificial Intelligence 41, 1 (1989), 1–63. [5] Dedre Gentner. 1983 …

Can we automate diagrammatic reasoning?
AA Sekh, DP Dogra, S Kar, PP Roy, DK Prasad – Pattern Recognition, 2020 – Elsevier
… Lovett et al. [26] have used computational model to solve RPMs. The method uses structural information such as shape, texture, etc. It then uses Structure-Mapping Engine to find the pattern variance among images. Finally, a set of rules is applied to find a solution. Ragni et al …

Knowledge, cognition, and everyday judgment: An introduction to the distributed semantics approach
R Richie, S Bhatia – 2020 – psyarxiv.com
… 2017). Future work could also attempt to directly integrate older cognitive process models of analogy and reasoning, such as the Structure Mapping Engine10 (Falkenhainer, Forbus, & Gentner, 1989), with representations for …

Analogical Proportions
C Anti? – arXiv preprint arXiv:2006.02854, 2020 – arxiv.org
Page 1. arXiv:2006.02854v1 [cs.LO] 4 Jun 2020 ANALOGICAL PROPORTIONS CHRISTIAN ANTIC Abstract. Analogy-making is at the core of human intelligence and creativity with appli- cations to such diverse tasks as commonsense …

Cogmic space for narrative-based world representation
T Akimoto – Cognitive Systems Research, 2021 – 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 …

Introduction
M Trench, RA Minervino – Distant Connections: The Memory Basis of …, 2020 – Springer
… Their computational models of mapping and inference generation (SME—structure mapping engine—Falkenhainer, Forbus, & Gentner, 1989; ACME—analogical constraint mapping engine—Holyoak & Thagard, 1989; LISA—learning and inference with schemas and analogies …

A Shared Framework of Reference, a First Step Toward Engineers’ and Biologists’ Synergic Reasoning in Biomimetic Design Teams
E Graeff, N Maranzana… – Journal of …, 2021 – asmedigitalcollection.asme.org
Skip to Main Content …

Closed Loop Neural-Symbolic Learning via Integrating Neural Perception, Grammar Parsing, and Symbolic Reasoning
Q Li, S Huang, Y Hong, Y Chen… – … on Machine Learning, 2020 – proceedings.mlr.press
Page 1. Closed Loop Neural-Symbolic Learning via Integrating Neural Perception, Grammar Parsing, and Symbolic Reasoning Qing Li 1 Siyuan Huang 1 Yining Hong 1 Yixin Chen 1 Ying Nian Wu 1 Song-Chun Zhu 1 Abstract …

Incidental binding between predictive relations
A Leshinskaya, M Bajaj, SL Thompson-Schill – Cognition, 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 …

Towards Qualitative Spatiotemporal Representations for Episodic Memory
W Hancock, KD Forbus, T Hinrichs – sme.uni-bamberg.de
… Too much, and learning is made more difficult because the space of hypotheses is larger. We use the Structure-Mapping Engine (SME; (Forbus et al., 2017)) to do comparisons and in analogical retrieval and generalization …

A uniform model of computational conceptual blending
M Schorlemmer, E Plaza – Cognitive Systems Research, 2021 – 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 …

Case-Based Reasoning, Analogy, and Interpolation
B Fuchs, J Lieber, L Miclet, A Mille, A Napoli… – A Guided Tour of …, 2020 – Springer
… 1993, Mitchell 2001). Structure mapping theory views an analogy as a mapping between a source and a target domain. The associated structure-mapping engine (SME) (Falkenhainer et al. 1989) returns the correspondences …

The relational processing limits of classic and contemporary neural network models of language processing
G Puebla, AE Martin, LAA Doumas – Language, Cognition and …, 2021 – Taylor & Francis
Whether neural networks can capture relational knowledge is a matter of long-standing controversy. Recently, some researchers have argued that (1) classic connectionist models can handle relational…

Artificial Intelligence and High-Level Cognition
M Ragni – A Guided Tour of Artificial Intelligence Research, 2020 – Springer
… A prominent model of analogical reasoning (as discussed in chapter “Case-Based Reasoning, Analogical Reasoning, Interpolation” of Volume 1) is the Structure Mapping Engine (SME), which proposes three steps in human analogy making (Gentner 1983; Falkenhainer et al …

MIT Media Laboratory
KB Haase – khaase.com
Page 1. Making Clouds from Cement: Building Abstractions around Concrete Examples Kenneth B. Haase MIT Media Laboratory This article discusses a radically memory-based representation where matches between con- crete …

Analogy and metareasoning: Cognitive strategies for robot learning
AK Goel, T Fitzgerald, P Parashar – Human-Machine Shared Contexts, 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 …

Analogical Comparison Promotes Theory?of?Mind Development
C Hoyos, WS Horton, NK Simms… – Cognitive Science, 2020 – Wiley Online Library
Abstract Theory?of?mind (ToM) is an integral part of social cognition, but how it develops remains a critical question. There is evidence that children can gain insight into ToM through experience,…

Creating Concepts: Considerations from Psychology and Artificial Intelligence
MM Hedblom – Image Schemas and Concept Invention, 2020 – Springer
Page 1. Chapter 1 Creating Concepts: Considerations from Psychology and Artificial Intelligence Abstract The symbol grounding problem is a prototypical problem in cognitive science and concerns how symbols gain their meaning …

How Multiple Exemplars Matter for Infant Spatial Categorization
M Casasola, Y Park – Language and Concept Acquisition from Infancy …, 2020 – Springer
The goal of the present chapter is to outline how infants’ experience with multiple exemplars contributes to their ability to form representations of the small-scale spatial relations, such as above,…

A survey on computational metaphor processing
S Rai, S Chakraverty – ACM Computing Surveys (CSUR), 2020 – dl.acm.org
Page 1. 24 A Survey on Computational Metaphor Processing SUNNY RAI, NSIT, University of Delhi, India and Mahindra École Centrale, India SHAMPA CHAKRAVERTY, Netaji Subhas University of Technology, India In the …

Boosting Retrieval Via Target Elaborations (the “Late Abstraction Principle”)
M Trench, RA Minervino – Distant Connections: The Memory Basis of …, 2020 – Springer
… 69–76). Hillsdale, NJ: Erlbaum.Google Scholar. Falkenhainer, B., Forbus, KD, & Gentner, D. (1989). The structure-mapping engine: Algorithm and examples. Artificial Intelligence, 41, 1–63.CrossRefGoogle Scholar. Finlayson, M., & Winston, P. (2006) …

8. The Grounded Simulation: Verbal and Visual Couplings
MV Deaca – The Control Cycle in Film, 2020 – content.sciendo.com
Page 1. 8. The Grounded Simulation: Verbal and Visual Couplings In “The Analytical Language of John Wilkins,” Borges describes: “a certain Chinese encyclopaedia entitled ‘Celestial Empire of Benevolent Knowledge’. In its …

An overview of distance and similarity functions for structured data
S Ontañón – Artificial Intelligence Review, 2020 – Springer
The notions of distance and similarity play a key role in many machine learning approaches, and artificial intelligence in general, since they can serve as.

Characterizing an Analogical Concept Memory for Newellian Cognitive Architectures
S Mohan, M Klenk, M Shreve, K Evans, A Ang… – arXiv preprint arXiv …, 2020 – arxiv.org
… To design the concept memory, we leverage the computational processes that underlie analogical rea- soning and generalization in the Companions cognitive architecture – the Structure Mapping Engine (SME; Forbus et al …

Analogical frames by constraint satisfaction
L De Vine – 2020 – eprints.qut.edu.au
Page 1. Analogical Frames by Constraint Satisfaction A THESIS SUBMITTED IN FULFILMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY Lance De Vine BMaths/BInfoTech, MInfTech (Research) School of Computer Science …

Ontologies and Concepts in Mind and Machine: 25th International Conference on Conceptual Structures, ICCS 2020, Bolzano, Italy, September 18-20, 2020 …
M Alam, T Braun, B Yun – 2020 – books.google.com
… objects in a two-dimensional space). References Falkenhainer, B., Forbus, KD, Gentner, D.: The structure-mapping engine: algorithm and examples. Artif. Intell. 41 (1), 1–63 (1989). https://doi. org/10.1016/0004-3702 (89) 90077 …

Multi-Modal Integration in Number Sense Acquisition
AX Yuan – 2020 – search.proquest.com
Multi-Modal Integration in Number Sense Acquisition. Abstract. Mathematical concepts usually have multiple representations. Even the simplest mathematical concepts, such as natural numbers, can be grounded in various ways …

Sketch Worksheets in Science, Technology, Engineering, and Mathematics Classrooms: Two Deployments
KD Forbus, B Garnier, B Tikoff, W Marko… – AI …, 2020 – search.proquest.com
… When students tackle the worksheet, they draw their sketch, which CogSketch analyzes and compares to the teacher’s sketch via a computational model of human analogy, the structure- mapping engine (SME), as will be explained …

Ontologies and Concepts in Mind and Machine
M Alam, T Braun, B Yun – Ontologies and Concepts in Mind and Machine …, 2020 – Springer
… objects in a two-dimensional space). References Falkenhainer, B., Forbus, KD, Gentner, D.: The structure-mapping engine: algorithm and examples. Artif. Intell. 41 (1), 1–63 (1989). https://doi. org/10.1016/0004-3702 (89) 90077 …

Relational rule discovery in complex discrimination learning.
HJ Don, MB Goldwater, JK Greenaway… – Journal of …, 2020 – psycnet.apa.org
Page 1. Journal of Experimental Psychology: Learning, Memory, and Cognition Relational Rule Discovery in Complex Discrimination Learning Hilary J. Don, Micah B. Goldwater, Justine K. Greenaway, Rosalind Hutchings, and …

Characterizing an Analogical Concept Memory for Architectures Implementing the Common Model of Cognition
S Mohan, M Klenk, COMM Shreve… – arXiv preprint arXiv …, 2020 – researchgate.net
… memories. To design the concept memory, we leverage the computational processes that underlie analogical reasoning and generalization in the Companions cognitive architecture – the Structure Mapping Engine (SME; Forbus et al …

The Processing of Non-nominal Metaphors
C Rodríguez Ronderos – 2021 – edoc.hu-berlin.de
… ERP . . . . . Event-related Potentials SPM . . . . . Standard Pragmatic Model SME . . . . . Structure Mapping Engine VWP . . . . . Visual World Paradigm xvii Page 20. 1 Introduction A fundamental property of language is that the meaning of words is predominantly stable …

Extracting invariant characteristics of sketch maps: Towards place query?by?sketch
M Tang, Z Falomir, C Freksa, Y Sheng… – Transactions in …, 2020 – Wiley Online Library
… adjacent glyphs based on that topological relationship. The shape similarity between corresponding glyphs is calculated using the SME (structure?mapping engine) algorithm. Wuersch and Egenhofer (2008) proposed a perceptual …

Analogical Theory of Mind: Computational Model and Applications
I Rabkina – 2020 – search.proquest.com
Page 1. NORTHWESTERN UNIVERSITY Analogical Theory of Mind: Computational Model and Applications A DISSERTATION SUBMITTED TO THE GRADUATE SCHOOL IN PARTIAL FULFILLMENT OF THE REQUIREMENTS for the degree DOCTOR OF PHILOSOPHY …

Distant Connections: The Memory Basis of Creative Analogy
M Trench, RA Minervino – 2020 – Springer
… Their computational models of mapping and inference generation (SME—structure mapping engine—Falkenhainer, Forbus, & Gentner, 1989; ACME—analogical con- straint mapping engine—Holyoak & Thagard, 1989; LISA—learning and inference with schemas and …

Computational philosophy
P Grim, D Singer – 2020 – stanford.library.sydney.edu.au

Qualitative Reasoning
JF Condotta, F Le Ber, G Ligozat… – A Guided Tour of Artificial …, 2020 – Springer
In this chapter, we discuss two research areas related to qualitative reasoning: firstly, qualitative reasoning about dynamical systems, or qualitative physics, that aims at providing qualitative…

The Stained Glass of Knowledge: On Understanding Novice Mental Models of Computing
BC Bettin – 2020 – digitalcommons.mtu.edu
Page 1. Michigan Technological University Digital Commons @ Michigan Tech Dissertations, Master’s Theses and Master’s Reports 2020 The Stained Glass of Knowledge: On Understanding Novice Mental Models of Computing …

Human-Machine Shared Contexts
W Lawless, R Mittu, D Sofge – 2020 – books.google.com
Page 1. HUMAN-MACHINE SHARED CONTEXTS Edited by William F. Lawless Ranjeev Mittu Donald A. Sofge Page 2. HUMAN-MACHINE SHARED CONTEXTS Page 3. This page intentionally left blank Page 4. HUMAN-MACHINE …

Perceptual and Linguistic Factors in Infants’ Relational Learning
EM Anderson – 2020 – search.proquest.com
Page 1. NORTHWESTERN UNIVERSITY Perceptual and Linguistic Factors in Infants’ Relational Learning A DISSERTATION SUBMITTED TO THE GRADUATE SCHOOL IN PARTIAL FULFILLMENT OF THE REQUIREMENTS for the degree DOCTOR OF PHILOSOPHY …

CogSketch v4. 16
K Forbus, M Usher, A Lovett, M Chang, M McLure… – qrg.northwestern.edu
Page 1. CogSketch v4.16 User Manual http://www.silccenter.org/ Ken Forbus Madeline Usher Andrew Lovett Maria Chang Matthew McLure Subu Kandaswamy Jon Wetzel Kate Lockwood Version of 12/21/2020 (Jupiter/Saturn Conjuction Release) …

Image schemas and concept invention: cognitive, logical, and linguistic investigations
MM Hedblom – 2020 – books.google.com
Page 1. Cognitive Technologies Maria M. Hedblom Image Schemas and Concept Invention Cognitive, Logical, and Linguistic Investigations Page 2. Cognitive Technologies Editor-in-chief Daniel Sonntag, DFKI, Saarbrücken, Saarland, Germany Page 3 …

A framework to communicate radically innovative material properties to designers
J Burchill – 2020 – bura.brunel.ac.uk
Page 1. A framework to communicate radically innovative material properties to designers. A thesis submitted for the degree of Doctor of Philosophy. By James Burchill Department of Design College of Engineering, Design and Physical Sciences Brunel University London …

Machine Perception MU—Visual Intelligence Tests
Z Les, M Les – Machine Understanding, 2020 – Springer
As it was shown in the previous Chapter visual intelligence tests belong to the category of the visual problems. Visual intelligence tests are series of tasks designed to measure the capacity to make…

A Computational Framework for Learning and Transforming Task Representations
AK Lampinen – 2020 – search.proquest.com
A Computational Framework for Learning and Transforming Task Representations. Abstract. Human cognition is fundamentally flexible — we can adapt to novel tasks rapidly. We can sometimes adapt to a novel task without any …