More than ever industry, space, and the military are seeking systems that can solve multiagent planning problems, such as those in supply chain management, coordinating space missions, and commanding mixtures of vehicles and troops. For many real-world problems it is hard to motivate multiple agents because centralized decision-making is often most efficient. One goal of this workshop is to identify methods for discerning how and when systems should be decentralized.
Multiagent planning and scheduling seems to fall in the intersection of the fields of planning and scheduling, distributed systems, parallel computing/algorithms, and multiagent systems. However, much of the research appears to build on ideas from either planning or multiagent systems (and usually not both). From the viewpoint of planning, planning for multiple agents means supporting concurrent action, and planning by multiple agents means parallelizing a planning algorithm. One might argue that the former has been done and the latter should be solved using parallel computing techniques and is dependent on hardware. On the other hand, from a multiagent systems perspective, multiagent planning is not about just solving planning problems but also how agents should behave and interact given that they have plans or planning capabilities.
From any point of view, there are many open issues in multiagent planning. While many planners can handle some notion of concurrency, and many plan merging algorithms have been proposed, there has been little work on decentralized planning, competitive planning systems, evaluation of communication costs, and distributed continual planning. We aim for this workshop to foster ideas addressing these issues and suggest other important research questions.
Format
The workshop will be one full day. We solicited papers and
position statements for presentation on topics including (but not
limited to)
We plan to have one or two invited speakers and a panel on applications where we hope to spur discussions among participants. In addition, we will set aside time after groups of related paper presentations to raise discussions pertinent to the talks.
Accepted Papers
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Extended Abstract: Honeywell' COORDINATORs Project
David J. Musliner and John Phelps |
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Managing Communication Limitations in Partially Controllable Multi-Agent Plans John Stedl and Brian Williams |
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Computing the Communication Costs of Item Allocation Timothy W. Rauenbusch, Stuart M. Shieber, and Barbara J. Grosz |
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Coordinating Agile Systems Through the Model-based Execution of Temporal Plans Thomas Léauté and Brian Williams |
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Execution Monitoring and Replanning with Incremental and Collaborative Scheduling David E. Wilkins, Stephen F. Smith, Laurence A. Kramer, Thomas J. Lee and Timothy W. Rauenbusch |
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Self-interested Planning Agents using Plan Repair Roman van der Krogt and Mathijs deWeerdt |
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Exploiting Interaction Structure in Networked Distributed POMDPs R. Nair, P. Varakantham, M. Tambe, and M. Yokoo |
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Bounded Policy Iteration for Decentralized POMDPs Daniel S. Bernstein, Eric A. Hansen, and Shlomo Zilberstein |
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ASET: a Multi-Agent Planning Language with Nondeterministic Durative Tasks for BDD-Based Fault Tolerant Planning Rune M. Jensen and Manuela M. Veloso |
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Robust Distributed Coordination of Heterogeneous Robots through Temporal Plan Networks Andreas F.Wehowsky, Stephen A. Block, and Brian C. Williams |
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Determining Task Valuations for Task Allocation David C. Han and K. Suzanne Barber |
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Planning for Multiagent Environments: From Individual Perceptions to Coordinated Execution Michael Brenner |
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From Multiagent Plan to Individual Agent Plans Olivier Bonnet-Torrès and Catherine Tessier |
Program Committee