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Information-Based Alpha-Beta Search and the Homicidal Chau.eur

  • Todd W. Neller
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2289)

Abstract

The standard means of applying a discrete search to a continuous or hybrid system is the uniform discretization of control actions and action timing. Such discretization is fixed a priori and does not allow search to benefit from information gained at run-time. This paper introduces Information-Based Alpha-Beta Search, a new algorithm that preserves and benefits from the continuous or hybrid nature of the search. In a novel merging of alpha-beta game-tree search and information-based optimization, Information-Based Alpha-Beta Search makes trajectorysampling decisions dynamically based on the maximum-likelihood of search pruning. The result is a search algorithm which, while incurring higher computational overhead for the optimization, manages to so increase the quality of the sampling, that the net effect is a significant increase in performance. We present a new piecewise-parabolic variant of the algorithm and provide empirical evidence of its performance relative to random and uniform discretizations in the context of a variant of the homicidal chauffeur game.

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References

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    Todd W. Neller. Information-based optimization approaches to dynamical system safety verification. In Thomas A. Henzinger and Shankar Sastry, editors, LNCS 1386: Hybrid Systems: computation and control, First International Workshop, HSCC’98, Proceedings, pages 346–359. Springer, Berlin, 1998.Google Scholar
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    Todd W. Neller. Simulation-Based Search for Hybrid System Control and Analysis. PhD thesis, Stanford University, Palo Alto, California, USA, June 2000. available as Stanford Knowledge Systems Laboratory technical report KSL-00-15 at http://www.ksl.stanford.edu.

Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • Todd W. Neller
    • 1
  1. 1.Department of Computer ScienceGettysburg CollegeGettysburgUSA

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