Metaphors and heuristic-driven theory projection (HDTP)

Gust, Helmar; Kühnberger, Kai‐Uwe; Schmid, Ute

doi:10.1016/j.tcs.2005.11.009

Cited by 38 publications

(16 citation statements)

References 8 publications

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“…FP Anti-Unification Input: Two terms f , g, and naturals l, m, p ∈ N. Problem: Is there an anti-unifier h, containing at least l 0-ary variables and at least m higher arity variables, and two substitutions σ, τ using only renamings, fixations, and at most p permutations such that h With respect to the original version of HDTP, [5] also offers some insight. As detailed in [12], instead of using restricted higher-order anti-unifications, HDTP initially was based on a mechanism reducing higher-order to first-order anti-unifications by introducing subterms built from what was called "admissible sequences":…”

Section: Previous Results On the Parametrized Complexity Of Hdtpmentioning

confidence: 99%

“…This line of work has resulted in several different frameworks for computational analogical reasoning, featuring systems as prominent as Hofstadter's Copycat [8] or the famous Structure-Mapping Engine (SME) [9] and MAC/FAC [10]. Whilst the latter two systems implement a version of Gentner's Structure-Mapping Theory (SMT) [11], more recently a different, generalization-based approach has been proposed: Heuristic-Driven Theory Projection (HDTP) [12,13].…”

Section: (In)tractability and Heuristic-driven Theory Projectionmentioning

confidence: 99%

“…The Heuristic-Driven Theory Projection framework [12] has been conceived as a mathematically sound framework for analogy-making. HDTP has been created for computing analogical relations and inferences for domains which are given in form of a manysorted first-order logic representation [14].…”

Section: Heuristic-driven Theory Projection For Computational Analogymentioning

confidence: 99%

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When Almost Is Not Even Close: Remarks on the Approximability of HDTP

Besold

Robere

2013

Artificial General Intelligence

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This is the accepted version of the paper.This version of the publication may differ from the final published version. Abstract. A growing number of researchers in Cognitive Science advocate the thesis that human cognitive capacities are constrained by computational tractability. If right, this thesis also can be expected to have far-reaching consequences for work in Artificial General Intelligence: Models and systems considered as basis for the development of general cognitive architectures with human-like performance would also have to comply with tractability constraints, making in-depth complexity theoretic analysis a necessary and important part of the standard research and development cycle already from a rather early stage. In this paper we present an application case study for such an analysis based on results from a parametrized complexity and approximation theoretic analysis of the Heuristic Driven Theory Projection (HDTP) analogy-making framework. Permanent

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Section: Previous Results On the Parametrized Complexity Of Hdtpmentioning

confidence: 99%

Section: (In)tractability and Heuristic-driven Theory Projectionmentioning

confidence: 99%

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When Almost Is Not Even Close: Remarks on the Approximability of HDTP

Besold

Robere

2013

Artificial General Intelligence

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“…ICARUS employs a representational mapping mechanism to transfer plan goal decompositions between different 2d grid games (Shapiro et al 2008). Kühnberger et al"s I-Cog (2008) explores the trade-offs between analogy and two other reasoning modules, all of which operate over noisy data, using the Heuristic-Driven Theory Projection (Gust et al 2006) model of analogy. Schwering et al (2008) identifies the importance of combining analogy with deductive and inductive techniques for achieving human level reasoning.…”

Section: Discussionmentioning

confidence: 99%

Domain transfer via cross-domain analogy

Klenk¹,

Forbus²

2009

Cognitive Systems Research

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“…A further heuristic in HDTP is the minimization of substitution lengths in the analogical relation, i.e. the simpler the analogy the better [27]. The motivation for this heuristic is to prevent arbitrary associations.…”

Section: Heuristic-driven Theory Projectionmentioning

confidence: 99%

Rationality in Context: An Analogical Perspective

Besold

2013

Modeling and Using Context

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This is the accepted version of the paper.This version of the publication may differ from the final published version. Abstract. At times, human behavior seems erratic and irrational. Therefore, when modeling human decision-making, it seems reasonable to take the remarkable abilities of humans into account with respect to rational behavior, but also their apparent deviations from the normative standards of rationality shining up in certain rationality tasks. Based on well-known challenges for human rationality, together with results from psychological studies on decision-making and from previous work in the field of computational modeling of analogy-making, I argue that the analysis and modeling of rational belief and behavior should also consider context-related cognitive mechanisms like analogy-making and coherence maximization of the background theory. Subsequently, I conceptually outline a high-level algorithmic approach for a Heuristic Driven Theory Projection-based system for simulating context-dependent human-style rational behavior. Finally, I show and elaborate on the close connections, but also on the significant differences, of this approach to notions of "ecological rationality". Permanent repository link:

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Metaphors and heuristic-driven theory projection (HDTP)

Cited by 38 publications

References 8 publications

When Almost Is Not Even Close: Remarks on the Approximability of HDTP

When Almost Is Not Even Close: Remarks on the Approximability of HDTP

Domain transfer via cross-domain analogy

Rationality in Context: An Analogical Perspective

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