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Peter Shell

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AAAI Conference 1994 Conference Paper

Improving Search through Diversity

Peter Shell

Adding diversity to symbolic search techniques has not been explored in artificial intelligence. Adding a diversity criterion provides us with a powerful new mechanism for finding global maxima in complex search spaces and helps to alleviate the problem of premature convergence to local maxima. A theoretical analysis is presented of issues in diversity searching which previously haven’ t been addressed, and a domain-independent diversity-search algorithm for practical breadth-first searching is developed. Empirical results of an implementation in the CRE- SUS expert system for intelligent cash-management confirm that diversity can significantly improve the solution quality of symbolic searchers.

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IJCAI Conference 1989 Conference Paper

Towards a General Framework for Composing Disjunctive and Iterative Macro-operators

Peter Shell
Jaime Carbonell

Inducing disjunctive and iterative macro-operators from empirical problem-solving traces provides a more powerful knowledge compilation method than simple linear macro-operators. Whereas earlier work focused on when to create iterative macro-operators, this paper addresses how to form them, combining proven optimization methods such as extraction of loop invariants, with techniques for further optimizing RETEmatch efficiency. The disjunctive and iterative composition processes have been implemented in FERMI and its underlying production system language. Empirical results confirm substantial rule-match speedups and system performance improvements in different application domains.

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