Abstract
Belief-Desire-Intention (BDI) agents are well suited for autonomous applications in dynamic environments. Their precompiled plan schemata contain the procedural knowledge of an agent and contribute to the performance. The agents generally are constrained to a fixed set of action patterns. Their choice depends on current goals, not on the future of the environment. Planning techniques can provide dynamic plans regarding the predicted state of the environment. We augment a BDI framework with a state-based planner for operational planning in domains where BDI is not well applicable. For this purpose, the requirements for the planner and for the coupling with a BDI system are investigated. An approach is introduced where a BDI system takes responsibility for plan monitoring and re-planning and the planner for the creation of plans. A fast state-based planner utilizing domain specific control knowledge retains the responsiveness of the system. In order to facilitate integration with BDI systems programmed in object-oriented languages, the planning problem is adopted into the BDI conceptual space with object-based domain models. The application of the hybrid system is illustrated using a propositional puzzle and a multi agent coordination scenario.
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References
Georgeff, M.P., Pell, B., Pollack, M., Tambe, M., Wooldrige, M.: The belief-desire-intention model of agency. In: Rao, A.S., Singh, M.P., Müller, J.P. (eds.) ATAL 1998. LNCS (LNAI), vol. 1555, pp. 1–10. Springer, Heidelberg (1999)
Bratman, M.E.: Intention, Plans, and Practical Reason. Harvard University Press, Cambrige (1987)
De Silva, L., Padgham, L.: A comparison of BDI based real-time reasoning and HTN based planning. In: Webb, G.I., Yu, X. (eds.) AI 2004. LNCS (LNAI), vol. 3339, pp. 1167–1173. Springer, Heidelberg (2004)
Bratman, M.E., Israel, D.J., Pollack, M.E.: Plans and resource-bounded practical reasoning. Computational Intelligence 4, 349–355 (1988)
Pokahr, A., Braubach, L., Lamersdorf, W.: A goal deliberation strategy for BDI agent systems. In: Eymann, T., Klügl, F., Lamersdorf, W., Klusch, M., Huhns, M.N. (eds.) MATES 2005. LNCS (LNAI), vol. 3550, Springer, Heidelberg (2005)
Shut, M., Wooldridge, M.: The control of reasoning in resource-bounded agents. The Knowledge Engineering Review 16(3) (2001)
Ghallab, M., Nau, D., Traverso, P.: Automated Planning: Theory and Practice. Morgan Kaufmann Publishers, San Francisco (2004)
Edelkamp, S., Hoffmann, J., Littman, M., Younes, H.: The 4th international planning competition 2004 (IPC-2004) Hosted at the International Conference on Automated Planning and Scheduling 2004 (ICAPS-2004) (2004)
Kvarnström, J., Magnusson, M.: TALplanner in IPC-2002: Extensions and control rules. Journal of Artificial Intelligence Research (JAIR) 20, 343–377 (2003)
Georgeff, M.P., Lansky, A.L.: Reactive reasoning and planning: An experiment with a mobile robot. In: Proceedings of the sixth National Conference on Artificial Intelligence (AAAI-87), Seattle, Washington, pp. 677–682 (1987)
Braubach, L., Pokahr, A., Moldt, D., Lamersdorf, W.: Goal representation for BDI agent systems. In: The Second International Workshop on Programming Multi Agent Systems, pp. 9–20 (2004)
Walczak, A.: Planning and the belief-desire-intention model of agency. Master’s thesis, University of Hamburg (2005)
Pokahr, A., Braubach, L., Lamersdorf, W.: Jadex: A BDI reasoning engine. In: Bordini, R., Dastani, M., Dix, J., Seghrouchni, A. (eds.) Multi-Agent Programming, Kluwer Academic Publishers, Dordrecht (2005)
Busetta, P., Ronnquist, R., Hodgson, A., Lucas, A.: JACK intelligent agent - components for intelligent agents in Java (1999)
FIPA: FIPA Contract Net Interaction Protocol Specification. FIPA (2001)
Fischer, K., Müller, J.P., Pischel, M.: Unifying control in a layered agent architecture. Technical Report TM-94-05, Deutsches Forschungszentrum für Künstliche Intelligenz GmbH, Kaiserslautern, DE (1994)
Despouys, O., Ingrand, F.F.: Propice-plan: Toward a unified framework for planning and execution. In: Biundo, S., Fox, M. (eds.) ECP 1999. LNCS, vol. 1809, pp. 278–293. Springer, Heidelberg (2000)
Wilkins, D.E., Myers, K.L., Wesley, L.P.: Cypress: Planning and reacting under uncertainity. In: Burstein, M.H. (ed.) ARPA/Rome Laboratory Planning and Scheduling Initiative Workshop Proceedings, Morgan Kaufmann, San Mateo (1994)
De Silva, L., Padgham, L.: Planning on demand in BDI systems. In: International Conference on Automated Planning and Scheduling, Monterey, California (2005)
Nau, D.S., Au, T.C., Ilghami, O., Kuter, U., Murdock, W., Wu, D., Yaman, F.: SHOP2: An HTN planning system. Journal of Artificial Intelligence Research 20, 379–404 (2003)
Fikes, R.E., Nilsson, N.J.: STRIPS: a new approach to the application of theorem proving to problem solving. Artificial Intelligence 2(3–4), 189–208 (1971)
Meneguzzi, F.R., Zorzo, A.F., da Costa Móra, M.: Propositional planning in BDI agents. In: Proceedings of the 2004 ACM symposium on Applied computing, pp. 58–63. ACM Press, New York (2004)
Móra, M.C., Lopes, J.G., Viccari, R.M., Coelho, H.: BDI models and systems: Reducing the gap. In: Rao, A.S., Singh, M.P., Müller, J.P. (eds.) ATAL 1998. LNCS (LNAI), vol. 1555, Springer, Heidelberg (1999)
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Walczak, A., Braubach, L., Pokahr, A., Lamersdorf, W. (2007). Augmenting BDI Agents with Deliberative Planning Techniques. In: Bordini, R.H., Dastani, M., Dix, J., Seghrouchni, A.E.F. (eds) Programming Multi-Agent Systems. ProMAS 2006. Lecture Notes in Computer Science(), vol 4411. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-71956-4_7
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DOI: https://doi.org/10.1007/978-3-540-71956-4_7
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-71955-7
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