Interleaved versus a priori exploration for repeated navigation in a partially-known graph

International Journal of Pattern Recognition and Artificial Intelligence

Volumn 13, Issue 7, 1999, Pages 963-986

  Argamon Engelson, Shlomo ^a   Kraus, Sarit ^b   Sina, Sigalit ^b  

^a JERUSALEM COLLEGE OF TECHNOLOGY   (Israel)

^b UNIVERSITY OF MARYLAND   (United States)

Author keywords

Expected utility; Exploration versus exploitation; Navigation; Random graphs

Indexed keywords

EID: 0348193571     PISSN: 02180014     EISSN: None     Source Type: Journal    
DOI: 10.1142/S0218001499000537     Document Type: Article

References (30)

1. S. Albers and M. R. Henzinger, "Exploring unknown environments," Proc. 29th Annual ACM Symp. Theory of Computing, 1997, pp. 416-425.
2. S. Argamon-Engelson, S. Kraus and S. Sina, "Utility-based on-line exploration for repeated navigation in an embedded graph," Artif. Intell. 102 (1998) 267-284.
3. C. B. Barber and H. Huhdanpaa, "Qhull software package, 1995," available at http://www.geom.umn.edu/software/qhull
4. K. Basye, T. Dean and J. S. Vitter, "Coping with uncertainty in map learning," Technical Report CS-89-27, Brown University Department of Computer Science, June 1989.
5. R. Bellman, Dynamic Programming, Princeton University Press, Princeton, NJ, 1957.
6. D. A. Berry and B. Fristedt, Bandit Problems: Sequential Allocation of Experiments, Chapman and Hall, London, UK, 1985.
7. D. P. Bertsekas, Dynamic Programming: Deterministic and Stochastic Models, Prentice-Hall, Englewood Cliffs, NJ, 1987.
8. M. Betke, R. L. Rivest and M. Singh, "Piecemeal learning of unknown environment," Mach. Learn. 18, 2&3 (1995) 231-254.
9. A. Blum and P. Chalasani, "An on-line algorithm for improving performance in navigation," Proc. Symp. Foundations of Computer Science, 1993, pp. 2-11.
10. B. Bollobas, Random Graphs, Academic Press, London, 1985.
11. F. Chimura and M. Tokoro, "The trailblazer search: a new method for searching and capturing moving targets," Proc. National Conf. Artificial Intelligence, 1994, pp. 1347-1352.
12. P. Cucka, N. S. Netanyahu and A. Rosenfeld, "Learning in navigation: goal finding in graphs," Int. J. Pattern Recognition and Artificial Intelligence 10, 5 (1996) 429-446.
13. T. Dean, D. Angluin, K. Basye, S. Engelson, L. Kaeloling, E. Kokkhevis and O. Maron, "Inferring finite automata with stochastic output functions and an application to map learning," Mach. Learn. 18, 1 (1995) 81-108.
14. T. Dean, L. P. Kaelbling, J. Kirman and A. Nicholson, "Planning under time constraints in stochastic domains," Artif. Intell. 76, 1&2 (1995) 35-74.
15. X. Deng and C. H. Papadimitriou, "Exploring an unknown graph," Proc. 31st Annual Symp. Foundations of Computer Science, IEEE Computer Society Press, 1990, pp. 355-361.
16. O. Etzioni, "Embedding decision-analytic control on a learning architecture," Artif. Intell. 49 (1991) 129-159.
17. P. Haddawy, A. Doan and R. Goodwin, "Efficient decision-theoretic planning: techniques and empirical analysis," Proc. Conf. Uncertainty in Artificial Intelligence, 1995, pp. 229-236.
18. T. Ishida and R. Korf, "A moving target search: a real-time search for changing goals," IEEE Trans. Patt. Anal. Mach. Intell. 17, 6 (1995) 609-619.
19. T. Ishida and M. Shimbo, "Improving the learning efficiencies of realtime search," Proc. National Conf. Artificial Intelligence, Portland, OR, 1996, pp. 305-310.
20. L. P. Kaelbling, Learning in Embedded Systems, The MIT Press, Cambridge, MA, 1993.
21. L. P. Kaelbling, M. L. Littman and A. W. Moore, "Reinforcement learning: a survey," J. Artif. Intell. Res. 4 (1996) 237-285.
22. G. I. Karakoulas, "Probabilistic exploration in planning while learning," eds. P. Besnard and S. Hanks, Eleventh Annual Conf. Uncertainty in Artificial Intelligence, 1995, pp. 352-361.
23. R. Korf, "Real-time heuristic search," Artif. Intell. 42, 2&3 (1990) 189-211.
24. A. W. Moore and C. G. Atkeson, "Prioritized sweeping: reinforcement learning with less data and less real time," Mach. Learn. 13 (1993) 103-130.
25. C. H. Papadimitrou and M. Yannakakis, "Shortest paths without a map," Theoret. Comput. Sci. 84, 1 (1991) 127-150.
26. M. L. Puterman, Markov Decision Processes: Discrete Stochastic Dynamic Programming, John Wiley, New York, 1994.
27. R. L. Rivest and R. E. Schapire, "Inference of finite automata using homing sequences (extended abstract)," Proc. Twenty-first Annual ACM Symp. Theory of Computing, Seattle, Washington, 1989, pp. 411-420.
28. Y. Smirnov, S. Koenig, M. M. Veloso and R. G. Simmons, "Efficient goal-directed exploration," Proc. National Conf. Artificial Intelligence, Portland, OR, 1996, pp. 292-297.
29. R. S. Sutton, "Integrated architectures for learning, planning, and reacting based on approximating dynamic programming," Proc. Seventh Int. Conf. Machine Learning, Austin, TX, 1990, Morgan Kaufmann, pp. 216-224
30. S. Thrun, "The role of exploration in learning control," Handbook for Intelligent Control: Neural, Fuzzy and Adaptive Approaches, Florence, Kentucky 41022, 1992, Van Nostrand Reinhold.