Abstract
We present a hybrid algorithm for distributed task allocation problem in a cooperative logistics domain. Our approach aims to achieve superior computational performance by combining the classic negotiation techniques and acquaintance models from agent technology field with methods from the operation research and AI planning. The algorithm is multi-stage and makes a clear separation between discreet planning that defines the tasks and allocation of resources to available tasks. Task allocation starts with centralized planning based on acquaintance model information that prepares a framework for efficient distributed negotiation. The subsequent distributed part of the task allocation process is parallel for all tasks and allows the agents to optimally allocate their resources to proposed tasks and to further optimize the allocation by negotiation with other agents. Parallel execution of the task allocation mechanism allows the algorithm to answer the planning request in predictable time, albeit at expense of possible non-optimality. In the experiments, we evaluate the relative importance of OR and negotiation parts of the task allocation process.
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Fischer, K., Muller, J.P., Pischel, M., Schier, D.: A model for cooperative transportation scheduling. In: Proceedings of the First International Conference on Multiagent Systems, Menlo park, California, pp. 109–116. AAAI Press / MIT Press (1995)
Perugini, D., Lambert, D., Sterling, L., Pearce, A.: A distributed agent approach to global transportation scheduling. In: The 2003 IEEE/WIC International Conference on Intelligent Agent Technology (IAT 2003), Halifax, Canada, pp. 18–24 (2003)
Smith, R.G.: The contract net protocol: High level communication and control in a distributed problem solver. IEEE Transactions on Computers C-29(12), 1104–1113 (1980)
Pĕchouc̆ek, M., Mařík, V., Bárta, J.: A knowledge-based approach to coalition formation. IEEE Intelligent Systems 17(3), 17–25 (2002)
Sandholm, T.: Contract types for satisficing task allocation: I theoretical results. In: Proceedings of the AAAI Spring Symposium (1998)
Perugini, D., Lambert, D., Sterling, L., Pearce, A.: Agent-based global transportation scheduling in military logistics. In: AAMAS 2004: Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems, pp. 1278–1279. IEEE Computer Society, Los Alamitos (2004)
Carlsson, C., Fullér, R.: Fuzzy Reasoning in Decision Making and Optimization. Physica Verlag, Springer, Heidelberg (2002)
Pechoucek, M., Mařík, V., Štěpánková, O.: Role of acquaintance models in agent-based production planning systems. In: Klusch, M., Kerschberg, L. (eds.) CIA 2000. LNCS (LNAI), vol. 1860, pp. 179–190. Springer, Heidelberg (2000)
Witteveen, C., Roos, N., van der Krogt, R., de Weerdt, M.: Diagnosis of single and multi-agent plans. In: AAMAS 2005: Proceedings of the fourth international joint conference on Autonomous agents and multiagent systems, pp. 805–812. ACM Press, New York (2005)
Miguel, I., Jarvis, P., Shen, Q.: Flexible graphplan. In: Horn, W. (ed.) Proceedings of the Fourteenth European Conference on Artificial Intelligence, pp. 506–510 (2000)
S̆is̆lák, D., Rehák, M., Pĕchouc̆ek, M., Rollo, M., Pavlíček, D.: A-globe: Agent development platform with inaccessibility and mobility support. In: Unland, R., Klusch, M., Calisti, M. (eds.) Software Agent-Based Applications, Platforms and Development Kits, pp. 21–46. Birkhäuser Verlag, Basel (2005)
Lawler, E.L., Wood, D.E.: Branch-and-bound methods: A survey. Operations Research 14(4), 699–719 (1966)
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Rehák, M., Volf, P., Pěchouček, M. (2006). Multilevel Approach to Agent-Based Task Allocation in Transportation. In: Klusch, M., Rovatsos, M., Payne, T.R. (eds) Cooperative Information Agents X. CIA 2006. Lecture Notes in Computer Science(), vol 4149. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11839354_20
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DOI: https://doi.org/10.1007/11839354_20
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