Abstract
In this paper we present a lightweight teamwork implementation by using abstraction hierarchies. The basis of this implementation is ADAPT, which supports Autonomous Dynamic Agent Planning for Teamwork. ADAPT’s novelty stems from how it succinctly decomposes teamwork problems into two separate planners: a task network for the set of activities to be performed by a specific agent and a separate group network for addressing team organization factors. Because abstract search techniques are the basis for creating these two components, ADAPT agents are able to effectively address teamwork in dynamic environments without explicitly enumerating the entire set of possible team states. During run-time, ADAPT agents then expand the teamwork states that are necessary for task completion through an association algorithm to dynamically link its task and group planners. As a result, ADAPT uses far fewer team states than existing teamwork models. We describe how ADAPT was implemented within a commercial training and simulation application, and present evidence detailing its success in concisely and effectively modeling teamwork.
Keywords
- Task Execution
- Group Network
- Complex Entity
- Task Network
- Mediator Agent
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
This research is based on work supported in part by Israel’s Ministry of Science and Technology grant # 44115.
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References
Bergmann, R., Wilke, W.: Building and refining abstract planning cases by change of representation language. JAIR 3, 53–118 (1995)
Grosz, B.J., Kraus, S.: Collaborative plans for complex group action. AIJ 86(2), 269–357 (1996)
Hadad, M., Kraus, S., Gal, Y., Lin, R.: Time reasoning for a collaborative planning agent in a dynamic environment. Annals of Math. and AI 37(4), 331–380 (2003)
Hoang, H., Lee-Urban, S., Muoz-Avila, H.: Hierarchical plan representations for encoding strategic game AI. In: AIIDE 2005. AAAI Press (2005)
Horling, B., Lesser, V., Vincent, R., Wagner, T., Raja, A., Zhang, S., Decker, K., Garvey, A.: The TAEMS White Paper (January 1999)
Kaminka, G.A., Frenkel, I.: Integration of coordination mechanisms in the BITE multi-robot architecture. In: ICRA 2007, pp. 2859–2866 (2007)
Mailler, R., Lesser, V.: Using Cooperative Mediation to Solve Distributed Constraint Satisfaction Problems. In: AAMAS 2004, pp. 446–453 (2004)
Muñoz-Ávila, H., McFarlane, D.C., Aha, D.W., Breslow, L., Ballas, J.A., Nau, D.S.: Using Guidelines to Constrain Interactive Case-Based HTN Planning. In: Althoff, K.-D., Bergmann, R., Branting, L.K. (eds.) ICCBR 1999. LNCS (LNAI), vol. 1650, pp. 288–302. Springer, Heidelberg (1999)
Nau, D., Ghallab, M., Traverso, P.: Automated Planning: Theory & Practice. Morgan Kaufmann Publishers Inc. (2004)
Nau, D.S., Au, T.-C., Ilghami, O., Kuter, U., Murdock, J.W., Wu, D., Yaman, F.: Shop2: An HTN planning system. J. Artif. Intell. Res (JAIR) 20, 379–404 (2003)
Pynadath, D.V., Tambe, M.: The communicative multiagent team decision problem: Analyzing teamwork theories and models. JAIR 16, 389–423 (2002)
Tambe, M.: Toward flexible teamwork. JAIR 7, 83–124 (1997)
Tambe, M., Pynadath, D.V., Chauvat, N., Das, A., Kaminka, G.A.: Adaptive agent integration architectures for heterogeneous team members, pp. 301–308 (2000)
Toseland, R.W., Rivas, R.F.: An Introduction to Group Work Practice. Allyn and Bacon (2001)
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Hadad, M., Rosenfeld, A. (2012). ADAPT: Abstraction Hierarchies to Better Simulate Teamwork under Dynamics. In: Beer, M., Brom, C., Dignum, F., Soo, VW. (eds) Agents for Educational Games and Simulations. AEGS 2011. Lecture Notes in Computer Science(), vol 7471. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32326-3_11
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DOI: https://doi.org/10.1007/978-3-642-32326-3_11
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