Computational complexities of honey-pot searching with local sensory information

Proceedings of the American Control Conference

Volumn 3, Issue , 2004, Pages 2134-2138

  Dasgupta, Bhaskar ^a   Hespanha, João P ^b   Sontag, Eduardo ^c  

^a University of Illinois at Chicago   (United States)

^b University of California   (United States)

^c RUTGERS UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; APPROXIMATION THEORY; COMPUTATIONAL COMPLEXITY; MOTION PLANNING; OPTIMIZATION; PROBABILITY; THEOREM PROVING;

APPROXIMATION ALGORITHMS; DEPTH-FIRST SEARCH (DFS); HONEY-POT SEARCHING;

PROBLEM SOLVING;

EID: 8744251037     PISSN: 07431619     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.23919/acc.2004.1383776     Document Type: Conference Paper

References (12)

1. th ACM-SIAM Symposium on Discrete Algorithms, 754-759, 2000.
2. X. Deng, T. Kameda and C. H. Papadimitriou. How to learn and unknown environment I: The rectilinear case, JACM, 45 (2), 215-245, March 1998.
3. J. P. Hespanha, H. J. Kim and S. Sastry. Multiple-Agent Probabilistic Pursuit-Evasion Games, Proceedings of the 38th IEEE Conference of Decision and Control, 3, 2432-2437, 1999.
4. J. P. Hespanha and H. Kizilocak. Efficient Computation of Dynamic Probabilistic Maps, 10th Mediterranean Conference on Control and Automata, July 2002.
5. A. Itai, C. H. Papadimitriou and J. L. Szwarcfiter. Hamiltonian Paths in Grid Graphs, SIAM Journal of Computing, 11 (4), 676-686, November 1982.
6. M. R. Garey, D. S. Johnson and R. E. Tarjan. The planar Hamiltonian circuit problem is NP-complete, SIAM Journal of Computing, 5, 704-714, 1976.
7. th Annual Symposium on Foundations of Computer Science, 302-309, 1996.
8. D. S. Johnson, M. Minkoff and S. Phillips. The prize collecting Steiner tree problem: theory and practice, 11th ACM-SIAM Symposium on Discrete Algorithms, 760-769, 2000.
9. L. D. Stone. Theory of Optimal Search, Academic Press, New York, 1975.
10. L. D. Stone. The Process of Search Planning: Current Approaches and Continuing Problems, Operation Research, 31, 207-233, 1983.
11. S. Thrun. Robotic Mapping: A Survey, in Exploring Artificial Intelligence in the New Millennium, G. Lakemeyer and B. Nebel (eds.), Morgan Kaufmann, 2002.
12. S. Thrun, W. Burgard and D. Fox. A probabilistic approach to concurrent mapping and localization for mobile robots, Machine Learning and Autonomous Robots (joint issue), 31 (5), 1-25, 1998.