19 found
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  1.  34
    The structure-mapping engine: Algorithm and examples.Brian Falkenhainer, Kenneth D. Forbus & Dedre Gentner - 1989 - Artificial Intelligence 41 (1):1-63.
  2.  20
    Qualitative process theory.Kenneth D. Forbus - 1984 - Artificial Intelligence 24 (1-3):85-168.
  3.  52
    MAC/FAC: A Model of Similarity‐Based Retrieval.Kenneth D. Forbus, Dedre Gentner & Keith Law - 1995 - Cognitive Science 19 (2):141-205.
    We present a model of similarity‐based retrieval that attempts to capture three seemingly contradictory psychological phenomena: (a) structural commonalities are weighed more heavily than surface commonalities in similarity judgments for items in working memory; (b) in retrieval, superficial similarity is more important than structural similarity; and yet (c) purely structural (analogical) remindings e sometimes experienced. Our model, MAC/FAC, explains these phenomena in terms of a two‐stage process. The first stage uses a computationally cheap, non‐structural matcher to filter candidate long‐term memory (...)
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  4.  27
    The Roles of Similarity in Transfer: Separating Retrievability from Inferential Soundness.Kenneth D. Forbus, Dedre Gentner & Mary Jo Rattermann - 1993 - Cognitive Psychology 25 (4).
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  5.  58
    Extending SME to Handle Large‐Scale Cognitive Modeling.Kenneth D. Forbus, Ronald W. Ferguson, Andrew Lovett & Dedre Gentner - 2017 - Cognitive Science 41 (5):1152-1201.
    Analogy and similarity are central phenomena in human cognition, involved in processes ranging from visual perception to conceptual change. To capture this centrality requires that a model of comparison must be able to integrate with other processes and handle the size and complexity of the representations required by the tasks being modeled. This paper describes extensions to Structure-Mapping Engine since its inception in 1986 that have increased its scope of operation. We first review the basic SME algorithm, describe psychological evidence (...)
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  6.  31
    Reviving Inert Knowledge: Analogical Abstraction Supports Relational Retrieval of Past Events.Dedre Gentner, Jeffrey Loewenstein, Leigh Thompson & Kenneth D. Forbus - 2009 - Cognitive Science 33 (8):1343-1382.
    We present five experiments and simulation studies to establish late analogical abstraction as a new psychological phenomenon: Schema abstraction from analogical examples can revive otherwise inert knowledge. We find that comparing two analogous examples of negotiations at recall time promotes retrieving analogical matches stored in memory—a notoriously elusive effect. Another innovation in this research is that we show parallel effects for real‐life autobiographical memory (Experiments 1–3) and for a controlled memory set (Experiments 4 and 5). Simulation studies show that a (...)
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  7.  12
    Cmpositional modeling: finding the right model for the job.Brian Falkenhainer & Kenneth D. Forbus - 1991 - Artificial Intelligence 51 (1-3):95-143.
  8.  18
    Qualitative spatial reasoning: The CLOCK project.Kenneth D. Forbus, Paul Nielsen & Boi Faltings - 1991 - Artificial Intelligence 51 (1-3):417-471.
  9.  28
    Expanding and Repositioning Cognitive Science.Paul S. Rosenbloom & Kenneth D. Forbus - 2019 - Topics in Cognitive Science 11 (4):918-927.
    Cognitive science has converged in many ways with cognitive psychology, but while also maintaining a distinctive interdisciplinary nature. Here we further characterize this existing state of the field before proposing how it might be reconceptualized toward a broader and more distinct, and thus more stable, position in the realm of sciences.
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  10.  31
    Incremental structure-mapping.Kenneth D. Forbus, Ronald W. Ferguson & Dedre Gentner - 1994 - In Ashwin Ram & Kurt Eiselt (eds.), Proceedings of the Sixteenth Annual Conference of the Cognitive Science Society: August 13 to 16, 1994, Georgia Institute of Technology. Erlbaum. pp. 313--318.
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  11. AI and Cognitive Science: The Past and Next 30 Years.Kenneth D. Forbus - 2010 - Topics in Cognitive Science 2 (3):345-356.
    Artificial Intelligence (AI) is a core area of Cognitive Science, yet today few AI researchers attend the Cognitive Science Society meetings. This essay examines why, how AI has changed over the last 30 years, and some emerging areas of potential interest where AI and the Society can go together in the next 30 years, if they choose.
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  12.  16
    CyclePad: An articulate virtual laboratory for engineering thermodynamics.Kenneth D. Forbus, Peter B. Whalley, John O. Everett, Leo Ureel, Mike Brokowski, Julie Baher & Sven E. Kuehne - 1999 - Artificial Intelligence 114 (1-2):297-347.
  13.  43
    The Cognitive Science of Sketch Worksheets.Kenneth D. Forbus, Maria Chang, Matthew McLure & Madeline Usher - 2017 - Topics in Cognitive Science 9 (4):921-942.
    Computational modeling of sketch understanding is interesting both scientifically and for creating systems that interact with people more naturally. Scientifically, understanding sketches requires modeling aspects of visual processing, spatial representations, and conceptual knowledge in an integrated way. Software that can understand sketches is starting to be used in classrooms, and it could have a potentially revolutionary impact as the models and technologies become more advanced. This paper looks at one such effort, Sketch Worksheets, which have been used in multiple classroom (...)
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  14.  14
    Qualitative process theory: twelve years after.Kenneth D. Forbus - 1993 - Artificial Intelligence 59 (1-2):115-123.
  15.  38
    Evidence from machines that learn and think like people.Kenneth D. Forbus & Dedre Gentner - 2017 - Behavioral and Brain Sciences 40.
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  16.  49
    Representation and Computation in Cognitive Models.Kenneth D. Forbus, Chen Liang & Irina Rabkina - 2017 - Topics in Cognitive Science 9 (3):694-718.
    One of the central issues in cognitive science is the nature of human representations. We argue that symbolic representations are essential for capturing human cognitive capabilities. We start by examining some common misconceptions found in discussions of representations and models. Next we examine evidence that symbolic representations are essential for capturing human cognitive capabilities, drawing on the analogy literature. Then we examine fundamental limitations of feature vectors and other distributed representations that, despite their recent successes on various practical problems, suggest (...)
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  17.  29
    An Analogical Model of Pretense.Irina Rabkina & Kenneth D. Forbus - 2022 - Cognitive Science 46 (3):e13112.
    Cognitive Science, Volume 46, Issue 3, March 2022.
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  18.  30
    Editors' Introduction: Sketching and Cognition.Kenneth D. Forbus & Shaaron Ainsworth - 2017 - Topics in Cognitive Science 9 (4):864-865.
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  19.  11
    Structure and interpretation of computer programs.Kenneth D. Forbus - 1985 - Artificial Intelligence 27 (1):124-127.
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