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

  • Authors:
  • Tarek Richard Besold;Robert Robere

  • Affiliations:
  • Institute of Cognitive Science, University of Osnabrück, Germany;Department of Computer Science, University of Toronto, Canada

  • Venue:
  • AGI'13 Proceedings of the 6th international conference on Artificial General Intelligence
  • Year:
  • 2013

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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.