Heuristic Selection for Stochastic Search Optimization: Modeling Solution Quality by Extreme Value Theory

Author:

Cicirello Vincent A.,Smith Stephen F.

Publisher

Springer Berlin Heidelberg

Reference24 articles.

1. Bresina, J.L.: Heuristic-biased stochastic sampling. In: Proceedings of the Thirteenth National Conference on Artificial Intelligence and the Eighth Innovative Applications of Artificial Intelligence Conference, vol. 1, pp. 271–278. AAAI Press, Menlo Park (1996)

2. Lecture Notes in Computer Science;V.A. Cicirello,2002

3. Cicirello, V.A.: Boosting Stochastic Problem Solvers Through Online Self-Analysis of Performance. PhD thesis, The Robotics Institute, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA (2003);

4. Also available as technical report CMU-RI-TR-03-27

5. Goldberg, D., Cicirello, V., Dias, M.B., Simmons, R., Smith, S., Stentz, A.: Market-based multi-robot planning in a distributed layered architecture. In: Multi-Robot Systems: From Swarms to Intelligent Automata: Proceedings of the 2003 International Workshop on Multi- Robot Systems, Washington, DC, vol. 2, pp. 27–38. Kluwer Academic Publishers, Dordrecht (2003)

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