Towards Domain-Independent Machine Intelligence

13 years 9 months ago
Towards Domain-Independent Machine Intelligence
Adaptive predictive search (APS), is a learning system framework, which given little initial domain knowledge, increases its decision-making abilities in complex problems domains. In this paper we give an entirely domain-independent version of APS that we are implementing in the PEIRCE conceptual graphs workbench. By using conceptual graphs as the \base language" a learning system is capable of re ning its own pattern language for evaluating states in the given domain that it nds itself in. In addition to generalizing APS to be domain-independent and CG-based we describe fundamental principles for the development of AI systems based on the structured pattern approach of APS. It is hoped that this e ort will lead the way to a more principled, and well-founded approach to the problems of mechanizing machine intelligence. The APS frameworkhas beenappliedto a numberof complexproblemdomains(includingchess, othello, pente and image alignment) where the combinatorics of the state space ...
Robert Levinson
Added 09 Aug 2010
Updated 09 Aug 2010
Type Conference
Year 1993
Where ICCS
Authors Robert Levinson
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