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When almost is not even close: Remarks on the approximability of HDTP

Besold, T. R. & Robere, R. (2013). When almost is not even close: Remarks on the approximability of HDTP. Lecture Notes in Computer Science, 7999 L, pp. 11-20. doi: 10.1007/978-3-642-39521-5_2


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.

Publication Type: Article
Additional Information: This is a post-peer-review, pre-copyedit version of an article published in Lecture Notes in Computer Science. The final authenticated version is available online at:
Departments: School of Science & Technology > Computer Science
SWORD Depositor:
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