Abstract
AI planning research has traditionally focused on offline pl- anning for static single-agent environments. In environments where an agent needs to plan its interactions with other autonomous agents, planning is much more complicated, because the actions of the other agents can induce a combinatorial explosion in the number of contingencies that the planner will need to consider. This paper discusses several ways to alleviate the combinatorial explosion, and illustrates their use in several different kinds of multi-agent planning domains.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Ghallab, M., Nau, D., Traverso, P.: Automated Planning: Theory and Practice. Morgan Kaufmann, San Francisco (2004)
Cimatti, A., Pistore, M., Roveri, M., Traverso, P.: Weak, strong, and strong cyclic planning via symbolic model checking. Artificial Intelligence 147(1-2), 35–84 (2003)
Pistore, M., Bettin, R., Traverso, P.: Symbolic techniques for planning with extended goals in non-deterministic domains. In: Proceedings of the European Conference on Planning (ECP) (2001)
Pistore, M., Traverso, P.: Planning as model checking for extended goals in non-deterministic domains. In: Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), Seattle, USA, pp. 479–484. Morgan Kaufmann, San Francisco (2001)
Bertoli, P., Cimatti, A., Pistore, M., Roveri, M., Traverso, P.: MBP: a model based planner. In: Proceeding of ICAI 2001 workshop on Planning under Uncertainty and Incomplete Information, Seattle, USA, pp. 93–97 (August 2001)
Bryant, R.E.: Symbolic boolean manipulation with ordered binary-decision diagrams. ACM Computing Surveys 24(3), 293–318 (1992)
Koenig, S., Simmons, R.G.: Real-time search in non-deterministic domains. In: IJCAI 1995 (1995)
Tate, A.: Project planning using a hierarchic non-linear planner. Technical Report 25, Department of Artificial Intelligence, University of Edinburgh (1976)
Sacerdoti, E.: A Structure for Plans and Behavior. American Elsevier, Amsterdam (1977)
Erol, K., Hendler, J., Nau, D.S.: Complexity results for hierarchical task-network planning. Annals of Mathematics and Artificial Intelligence 18, 69–93 (1996)
Kambhampati, S.: Are we comparing Dana and Fahiem or SHOP and TLPlan? a critique of the knowledge-based planning track at ICP (2003), http://rakaposhi.eas.asu.edu/kbplan.pdf
Nau, D.: Current trends in automated planning. AI Magazine 28(4), 43–58 (2007)
Kuter, U., Nau, D.: Forward-chaining planning in nondeterministic domains. In: Proceedings of the National Conference on Artificial Intelligence (AAAI), pp. 513–518 (July 2004)
Kuter, U., Nau, D., Pistore, M., Traverso, P.: A hierarchical task-network planner based on symbolic model checking. In: Proceedings of the International Conference on Automated Planning and Scheduling (ICAPS), pp. 300–309 (June 2005)
Kuter, U., Nau, D., Pistore, M., Traverso, P.: Task decomposition on abstract states, for planning under nondeterminism. Artificial Intelligence (to appear, 2008)
Korf, R.: Real-time heuristic search. Artificial Intelligence 42(2–3), 189–211 (1990)
Hoffmann, J., Nebel, B.: The FF planning system: Fast plan generation through heuristic search. Journal of Artificial Intelligence Research 14, 253–302 (2001)
Bacchus, F., Kabanza, F.: Using temporal logics to express search control knowledge for planning. Artificial Intelligence 116(1-2), 123–191 (2000)
Nau, D.S., Muñoz-Avila, H., Cao, Y., Lotem, A., Mitchell, S.: Total-order planning with partially ordered subtasks. In: Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), Seattle (August 2001)
Dix, J., Muñoz-Avila, H., Nau, D.S., Zhang, L.: IMPACTing SHOP: Planning in a multi-agent environment. In: Sadri, F., Satoh, K. (eds.) Proc. Second Workshop on Computational Logic and Multi-Agent Systems (CLIMA), London, Imperial College, pp. 30–42 (July 2000)
Bratman, M.E.: Intentions, Plans, and Practical Reason. Harvard University Press (1987)
Georgeff, M.P., Lansky, A.L.: Reactive reasoning and planning. In: Proceedings of the National Conference on Artificial Intelligence (AAAI), pp. 677–682 (1987); reprinted in [47], pp. 729–734
Rao, A.S.: AgentSpeak(L): BDI agents speak out in a logical computable language. In: van Hoe, R. (ed.) Seventh European Workshop on Modelling Autonomous Agents in a Multi-Agent World, Eindhoven, The Netherlands (1996)
Firby, R.J.: Adaptive execution in complex dynamic worlds. PhD thesis 672, Yale University (1989)
Sardiña, S., de Silva, L., Padgham, L.: Hierarchical planning in BDI agent programming languages: A formal approach. In: AAMAS, Hakodate, Japan, pp. 1001–1008 (May 2006)
Sardiña, S., Padgham, L.: Goals in the context of BDI plan failure and planning. In: AAMAS, Honolulu, HI, pp. 16–24 (May 2007)
Billings, D.: The first international RoShamBo programming competition. ICGA Journal 23(1), 42–50 (2000)
Billings, D.: Thoughts on RoShamBo. ICGA Journal 23(1), 3–8 (2000)
Billings, D.: The second international roshambo programming competition (2001), http://www.cs.ualberta.ca/~darse/rsbpc.html
Li, D.: Kriegspiel: Chess Under Uncertainty. Premier (1994)
Li, D.: Chess Detective: Kriegspiel Strategies, Endgames and Problems. Premier (1995)
Parker, A., Nau, D., Subrahmanian, V.: Overconfidence or paranoia? search in imperfect-information games. In: Proceedings of the National Conference on Artificial Intelligence (AAAI) (July 2006)
Boutilier, C., Dean, T.L., Hanks, S.: Decision-theoretic planning: Structural assumptions and computational leverage. Journal of Artificial Intelligence Research 11, 1–94 (1999)
Aumann, R.: Acceptable points in general cooperative n-person games. In: Luce, R.D., Tucker, A.W. (eds.) Contributions to the Theory of Games, vol. 4. Princeton University Press, Princeton (1959)
Axelrod, R.: The Evolution of Cooperation. Basic Books (1984)
Au, T.C., Nau, D.: Accident or intention: That is the question (in the iterated prisoner’s dilemma). In: International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS) (2006)
Au, T.C., Nau, D.: Is it accidental or intentional? a symbolic approach to the noisy iterated prisoner’s dilemma. In: Kendall, G., Yao, X., Chong, S.Y. (eds.) The Iterated Prisoners Dilemma: 20 Years On, pp. 231–262. World Scientific, Singapore (2007)
Axelrod, R., Dion, D.: The further evolution of cooperation. Science 242(4884), 1385–1390 (1988)
Bendor, J.: In good times and bad: Reciprocity in an uncertain world. American Journal of Politicial Science 31(3), 531–558 (1987)
Bendor, J., Kramer, R.M., Stout, S.: When in doubt.. cooperation in a noisy prisoner’s dilemma. The Jour. of Conflict Resolution 35(4), 691–719 (1991)
Molander, P.: The optimal level of generosity in a selfish, uncertain environment. The Journal of Conflict Resolution 29(4), 611–618 (1985)
Mueller, U.: Optimal retaliation for optimal cooperation. The Journal of Conflict Resolution 31(4), 692–724 (1987)
Nowak, M., Sigmund, K.: The evolution of stochastic strategies in the prisoner’s dilemma. Acta Applicandae Mathematicae 20, 247–265 (1990)
Kendall, G., Yao, X., Chong, S.Y.: The Iterated Prisoner’s Dilemma: 20 Years On. World Scientific, Singapore (2007)
Au, T.C., Nau, D.: An analysis of derived belief strategy’s performance in the 2005 iterated prisoner’s dilemma competition. Technical Report CSTR-4756/UMIACS-TR-2005-59, University of Maryland, College Park (2005)
Smith, S.J.J., Nau, D.S., Throop, T.: A planning approach to declarer play in contract bridge. Computational Intelligence 12(1), 106–130 (1996)
Allen, J.F., Hendler, J., Tate, A. (eds.): Readings in Planning. Morgan Kaufmann, San Francisco (1990)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Au, TC., Kuter, U., Nau, D. (2009). Planning for Interactions among Autonomous Agents. In: Hindriks, K.V., Pokahr, A., Sardina, S. (eds) Programming Multi-Agent Systems. ProMAS 2008. Lecture Notes in Computer Science(), vol 5442. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03278-3_1
Download citation
DOI: https://doi.org/10.1007/978-3-642-03278-3_1
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-03277-6
Online ISBN: 978-3-642-03278-3
eBook Packages: Computer ScienceComputer Science (R0)