Strong planning under partial observability

Artificial Intelligence

Volumn 170, Issue 4-5, 2006, Pages 337-384

  Bertoli, Piergiorgio ^a   Cimatti, Alessandro ^a   Roveri, Marco ^a   Traverso, Paolo ^a  

^a ITC IRST   (Italy)

Author keywords

Binary decision diagrams; Heuristic search in belief space; Planning in nondeterministic domains; Planning under partial observability; Symbolic model checking

Indexed keywords

BENCHMARKING; COMPUTER SIMULATION; GENETIC ALGORITHMS; PLANNING; PROBLEM SOLVING; SEARCH ENGINES;

BINARY DECISION DIAGRAMS; HEURISTIC SEARCH IN BELIEF SPACE; PLANNING IN NONDETERMINISTIC DOMAINS; PLANNING UNDER PARTIAL OBSERVABILITY; SYMBOLIC MODEL CHECKING;

INTELLIGENT NETWORKS;

EID: 32944468402     PISSN: 00043702     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.artint.2006.01.004     Document Type: Article

References (89)

1. A. Albore, and P. Bertoli Generating safe assumption-based plans for partially observable, nondeterministic domains Proceedings of AAAI-04 Seattle, WA 2004 AAAI Press
2. F. Bacchus, C. Boutilier, A.J. Grove, Rewarding behaviors, in: Proceedings of AAAI-96, Portland, OR, 1996
3. F. Bacchus, C. Boutilier, A.J. Grove, Structured solution methods for non-Markovian decision processes, in: Proceedings of AAAI-97, Providence, RI, 1997
4. 20 states and beyond Inform. and Comput. 98 2 1992 142 170
5. P. Bertoli, A. Cimatti, M. Pistore, M. Roveri, P. Traverso, MBP: a model based planner, in: Proceeding of ICAI-2001 workshop on Planning under Uncertainty and Incomplete Information, Seattle, WA, 2001, pp. 93-97
6. P. Bertoli, A. Cimatti, M. Pistore, P. Traverso, A framework for planning with extended goals and partial observability, in: Proceedings of ICAPS-03, 2003
7. P. Bertoli, A. Cimatti, M. Roveri, Conditional planning under partial observability as heuristic-symbolic search in belief space, in: Proceedings of the European Conference on Planning (ECP), 2001
8. P. Bertoli, A. Cimatti, and M. Roveri Heuristic search + symbolic model checking = efficient conformant planning B. Nebel Proceedings of the Seventeenth International Joint Conference on Artificial Intelligence, IJCAI 2001 2001 Morgan Kaufmann 467 472
9. P. Bertoli, A. Cimatti, M. Roveri, and P. Traverso Planning in nondeterministic domains under partial observability via symbolic model checking Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI) Seattle, WA 2001 Morgan Kaufmann 473 478
10. P. Bertoli, A. Cimatti, J. Slaney, S. Thiebaux, solving power supply restoration problems with planning via model checking, in: Proceedings of ECAI-02, 2002
11. P. Bertoli, A. Cimatti, P. Traverso, Interleaving execution and planning for nondeterministic, partially observable domains, in: Proceedings of ECAI-04, 2004
12. C. Boutilier, T. Dean, and S. Hanks Decision-theoretic planning: structural assumptions and computational leverage J. Artificial Intelligence Res. (JAIR) 11 1 1999 1 94
13. A.L. Blum, and M.L. Furst Fast planning through planning graph analysis Artificial Intelligence 1-2 90 1997 279 298
14. B. Bonet, H. Geffner, Learning sorting and decision trees with POMDPs, in: Proceedings of the International Conference on Machine Learning (ICML), 1998
15. B. Bonet, and H. Geffner Planning with incomplete information as heuristic search in belief space S. Chien S. Kambhampati C.A. Knoblock 5th International Conference on Artificial Intelligence Planning and Scheduling 2000 AAAI Press 52 61
16. B. Bonet, and H. Geffner Planning with incomplete information as heuristic search in belief space Proceedings of AIPS-00 2000 AAAI Press 52 61
17. B. Bonet, and H. Geffner Labeled RTDP: improving the convergence of real-time dynamic programming Proceedings of ICAPS-03 2003 AAAI Press 12 21
18. B. Bonet, H. Geffner, An algorithm better than AO*, in: Proceedings of 20th National Conf. on Artificial Intelligence (AAAI-05), 2005, pp. 1343-1348
19. R. Brafman, J. Hoffmann, Conformant planning via heuristic forward search: a new approach, in: Proceedings of ICAPS-04, 2004
20. F. Bacchus, and F. Kabanza Using temporal logic to express search control knowledge for planning Artificial Intelligence 116 1 2000 123 191
21. D. Bryce, S. Kambhampati, Heuristic guidance measures for conformant planning, in: Proceedings of ICAPS'03 Workshop on Planning under Uncertainty and Incomplete Information, Trento, Italy, 2003
22. C. Boutilier, A POMDP formulation of preference elicitation problems, in: AAAI/IAAI Proceedings, 2002
23. P. Bertoli, M. Pistore, Planning with extended goals and partial observability, in: Proceedings of ICAPS-04, 2004
24. K.S. Brace, R.L. Rudell, and R.E. Bryant Efficient implementation of a BDD package 27th ACM/IEEE Design Automation Conference Orlando, FL 1990 ACM/IEEE, IEEE Computer Society Press 40 45
25. R.E. Bryant Graph-based algorithms for boolean function manipulation IEEE Trans. Comput. C-35 8 1986 677 691
26. R.E. Bryant On the complexity of VLSI implementations and graph representations of boolean functions with application to integer multiplication IEEE Trans. Comput. 40 2 1991 205 213
27. R.E. Bryant Symbolic boolean manipulation with ordered binary-decision diagrams ACM Comput. Surv. 24 3 1992 293 318
28. B. Bonet, and S. Thiebaux GPT meets PSR Proceedings of ICAPS-03 2003 AAAI Press 102 111
29. A. Cimatti, E.M. Clarke, F. Giunchiglia, and M. Roveri NuSMV: a new symbolic model checker Internat. J. Software Tools Technol. Transfer (STTT) 2 4 2000
30. E.M. Clarke, E.A. Emerson, and A.P. Sistla Automatic verification of finite-state concurrent systems using temporal logic specifications ACM Trans. Programming Languages Systems 8 2 1986 244 263
31. C. Castellini, E. Giunchiglia, and A. Tacchella SAT-based planning in complex domains: concurrency, constraints and nondeterminism Artificial Intelligence J. 147 1,2 2003 85 117
32. A. Cassandra, L. Kaelbling, and M. Littman Acting optimally in partially observable stochastic domains Proceedings of AAAI-94 1994 AAAI Press
33. O. Coudert, J.C. Madre, H. Touati, TiGeR version 1.0 user guide, Digital Paris Research Lab, December 1993
34. A. Cimatti, M. Pistore, M. Roveri, and P. Traverso Weak, strong, and strong cyclic planning via symbolic model checking Artificial Intelligence 147 1-2 2003 35 84
35. A. Cimatti, and M. Roveri Conformant planning via symbolic model checking J. Artificial Intelligence Res. (JAIR) 13 2000 305 338
36. A. Cimatti, M. Roveri, and P. Bertoli Conformant planning via symbolic model checking and heuristic search Artificial Intelligence 159 1-2 2004 127 206
37. A. Cimatti, M. Roveri, and P. Traverso Strong planning in non-deterministic domains via model checking Proceedings of AIPS-98 1998 AAAI Press
38. E.M. Clarke, and J.M. Wing Formal methods: state of the art and future directions ACM Comput. Surv. 28 4 1996 626 643
39. U. Dal Lago, M. Pistore, and P. Traverso Planning with a language for extended goals Proceedings of the Eighteenth National Conference on Artificial Intelligence (AAAI-02) Edmonton, Alberta 2002 AAAI Press/MIT Press 447 454
40. G. De Giacomo, and M.Y. Vardi Automata-theoretic approach to planning for temporally extended goals S. Biundo (Ed.) Proceeding of the Fifth European Conference on Planning Durham, UK Lecture Notes in Artificial Intelligence 1999 Springer-Verlag
41. T. Eiter, W. Faber, N. Leone, G. Pfeifer, and A. Polleres A logic programming approach to knowledge-state planning Artificial Intelligence 144 1-2 2003 157 211
42. S. Edelkamp, M. Helmert, On the implementation of MIPS, in: AIPS-Workshop on Model-Theoretic Approaches to Planning, 2000, pp. 18-25
43. R. Fagin, J.Y. Halpern, Y. Moses, and M.Y. Vardi Reasoning about Knowledge 1995 MIT Press
44. Goldsmith, M. Mundhenk, Complexity issues in Markov decision processes, in: Proceedings of 13th Conference on Computational Complexity, 1998
45. R.P. Goldman, D.J. Musliner, K.D. Krebsbach, and M.S. Boddy Dynamic abstraction planning Proceedings of the Fourteenth National Conference on Artificial Intelligence and Ninth Innovative Applications of Artificial Intelligence Conference (AAAI 97), (IAAI 97) 1997 AAAI Press 680 686
46. R.P. Goldman, D.J. Musliner, M.J. Pelican, Using model checking to plan hard real-time controllers, in: Proceeding of the AIPS2k Workshop on Model-Theoretic Approaches to Planning, Breckeridge, CO, 2000
47. M. Genesereth, I. Nourbakhsh, Time-saving tips for problem solving with incomplete information, in: Proceedings of the National Conference on Artificial Intelligence, 1993
48. R.P. Goldman, M. Pelican, D.J. Musliner, Hard real-time mode logic synthesis for hybrid control: a CIRCA-based approach, 1999. Working notes of the 1999 AAAI Spring Symposium on Hybrid Control
49. N. Hyafil, F. Bacchus, Conformant probabilistic planning via CSPs, in: Proceedings of ICAPS-03, 2003
50. J. Hoffmann, R. Brafman, Contingent planning via heuristic forward search with implicit belief states, in: Proceedings of ICAPS-05, 2005
51. A. Herzig, J. Lang, P. Marquis, Action representation and partially observable planning using epistemic logic, in: Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI-03), Acapulco, Mexico, 2003
52. J. Hoey, R. St-Aubin, A. Hu, and C. Boutilier SPUDD: Stochastic planning using decision diagrams K.B. Laskey H. Prade Proceedings of the 15th Conference on Uncertainty in Artificial Intelligence (UAI-99) San Francisco, CA 1999 Morgan Kaufmann 279 288
53. E.A. Hansen, and S. Zilberstein LAO*: a heuristic search algorithm that finds solutions with loops Artificial Intelligence 129 1-2 2001 35 62
54. P. Jimenez, and C. Torras An efficient algorithm for searching implicit AND/OR graphs with cycles Artificial Intelligence 124 2000 1 30
55. R.M. Jensen, and M.M. Veloso OBDD-based universal planning for synchronized agents in non-deterministic domains J. Artificial Intelligence Res. (JAIR) 13 2000 189 226
56. R.M. Jensen, M.M. Veloso, M.H. Bowling, OBDD-based optimistic and strong cyclic adversarial planning, in: Proceedings of ECP-01, 2001
57. L. Karlson Conditional progressive planning under uncertainty Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI) Seattle, WA 2001 Morgan Kaufmann
58. F. Kabanza, M. Barbeau, and R. St-Denis Planning control rules for reactive agents Artificial Intelligence 95 1 1997 67 113
59. N. Kushmerick, S. Hanks, and D. Weld An algorithm for probabilistic planning Artificial Intelligence 76 1-2 1995 239 286
60. L. Kaelbling, M. Littman, and A. Cassandra Planning and acting in partially observable stochastic domains Artificial Intelligence 101 1-2 1998 99 134
61. H.A. Kautz, B. Selman, Pushing the envelope: planning, propositional logic, and stochastic search, in: Proceedings of AAAI-96, Portland, OR, 1996
62. S. Koenig, and R. Simmons Solving robot navigation problems with initial pose uncertainty using real-time heuristic search R.G. Simmons M. Veloso S. Smith Proceedings of the Second International Conference on Artificial Intelligence Planning Systems (AIPS-98) 1998 AAAI Press 145 153
63. A. Mahanti, and A. Bagchi AND/OR graph heuristics search methods J. ACM 32 1 1985 28 51
64. K.L. McMillan Symbolic Model Checking 1993 Kluwer Academic
65. S. Majercik, M. Littman, MAXPLAN: a new approach to probabilistic planning, in: Proceedings of AIPS-1998, 1998
66. A. Martelli, U. Montanari, Additive AND/OR graphs, in: Proceedings of IJCAI-73, Stanford, CA, 1973, pp. 1-11
67. A. Martelli, and U. Montanari Optimising decision trees through heuristically guided search Comm. ACM 21 12 1978 1025 1039
68. N.J. Nillson Principles of Artificial Intelligence 1980 Tioga Publishing Company
69. P. Poupart, C. Boutilier, Value-directed belief state approximation for POMDPs, in: Proceedings of the Conference on Uncertainty in Artificial Intelligence (UAI), 2000
70. P. Poupart, C. Boutilier, Vector-space analysis of belief-state approximation for POMDPs, in: Proceedings of the Conference on Uncertainty in Artificial Intelligence (UAI), 2001
71. R. Petrick, F. Bacchus, A knowledge-based approach to planning with incomplete information and sensing, in: Proceedings of the Sixth International Conference on Artificial Intelligence Planning and Scheduling (AIPS-02), 2002
72. R. Petrick, F. Bacchus, Extending the knowledge-based approach to planning with incomplete information and sensing, in: Proceedings of the International Conference on Automated Planning and Scheduling (ICAPS-04), 2004, pp. 2-11
73. L. Pryor, and G. Collins Planning for contingency: a decision based approach J. Artificial Intelligence Res. 4 1996 81 120
74. M. Peot, and D. Smith Conditional nonlinear planning J. Hendler Proceedings of the First International Conference on AI Planning Systems College Park, MD 1992 Morgan Kaufmann 189 197
75. C.H. Papadimitriou, and J.N. Tsitsiklis The complexity of Markov decision processes Math. Oper. Res. 12 3 1987 441 450
76. M. Pistore, P. Traverso, Planning as model checking for extended goals in non-deterministic domains, in: Proceedings of IJCAI-01, Seattle, WA, 2001
77. J. Rintanen Constructing conditional plans by a theorem-prover J. Artificial Intellegence Res. 10 1999 323 352
78. J. Rintanen Improvements to the evaluation of quantified boolean formulae T. Dean 16th International Joint Conference on Artificial Intelligence 1999 Morgan Kaufmann 1192 1197
79. J. Rintanen, Backward plan construction for planning as search in belief space, in: Proceedings of the International Conference on AI Planning and Scheduling (AIPS), 2002
80. J. Rintanen Complexity of planning with partial observability Proceedings of the 14th International Conference on Automated Planning and Scheduling (ICAPS'04) 2004 AAAI Press 345 354
81. J. Rintanen Research on conditional planning with partial observability: the jussi-POP/BBSP planning system http://www.informatik.uni-freiburg.de/ rintanen/planning.html 2004
82. F. Somenzi, CUDD: CU decision diagram package - release 2.1.2. Department of Electrical and Computer Engineering - University of Colorado at Boulder, April 1997
83. E.J. Sondik The optimal control of partially observable Markov decision processes over the infinite horizon: discounted costs Oper. Res. 26 2 1978 282 304
84. S. Thiebaux, M.O. Cordier, Supply restoration in power distribution systems: a benchmark for planning under uncertainty, in: Proceedings of ECP-01, 2001
85. S. Thiebaux, J. Hoffmann, and B. Nebel In defense of PDDL axioms Proceedings of 18th International Joint Conference on Artificial Intelligence (IJCAI-03) Acapulco, Mexico 2003 Morgan Kaufmann
86. C. Tovey, and S. Koenig Gridworlds as testbeds for planning with incomplete information Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence 2000 AAAI Press 819 824
87. S. Thiebaux, F. Kabanza, J. Slaney, Anytime state-based solution methods for decision processes with non-Markovian rewards, in: Proceedings of the Conference on Uncertainty in Artificial Intelligence (UAI), 2002
88. D.S. Weld, C.R. Anderson, and D.E. Smith Extending graphplan to handle uncertainty and sensing actions and sensing actions Proceedings of the 15th National Conference on Artificial Intelligence (AAAI-98) and of the 10th Conference on Innovative Applications of Artificial Intelligence (IAAI-98) Menlo Park, CA 1998 AAAI Press 897 904
89. B. Yang, R.E. Bryant, D.R. O'Hallaron, A. Biere, O. Coudert, G. Janssen, R.K. Ranjan, F. Somenzi, A performance study of BDD-Based model checking, in: Proceedings of the Formal Methods on Computer-Aided Design, 1998, pp. 255-289