Coalitions among computationally bounded agents
Artificial Intelligence - Special issue on economic principles of multi-agent systems
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
TALplanner: A temporal logic based forward chaining planner
Annals of Mathematics and Artificial Intelligence
A Market Protocol for Decentralized Task Allocation
ICMAS '98 Proceedings of the 3rd International Conference on Multi Agent Systems
Efficient Mechanisms for Multiagent Plan Merging
AAMAS '04 Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 3
Coordinating Self-interested Planning Agents
Autonomous Agents and Multi-Agent Systems
Distributed management of flexible times schedules
Proceedings of the 6th international joint conference on Autonomous agents and multiagent systems
Efficient implementation of the plan graph in STAN
Journal of Artificial Intelligence Research
Methods for task allocation via agent coalition formation
Artificial Intelligence
Framework and complexity results for coordinating non-cooperative planning agents
MATES'06 Proceedings of the 4th German conference on Multiagent System Technologies
Improving task-based plan coordination
CARE@AI'09/CARE@IAT'10 Proceedings of the CARE@AI 2009 and CARE@IAT 2010 international conference on Collaborative agents - research and development
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Task-based planning problems for multi-agent systems require multiple agents to find a joint plan for a constrained set of tasks. Typically, each agent receives a subset of tasks to complete. Due to task interdependencies, such task allocations induce interdependencies between agents as well. These interdependencies will prevent the agents from making a plan for their subset of tasks independently from each other, since the combination of such autonomously constructed plans will most probably result in conflicting plans. Therefore, a plan-coordination mechanism is needed to guarantee a conflict-free globally feasible plan. In this paper, we first present a brief overview of the main results achieved on plan coordination for autonomous planning agents, distinguishing between problems associated with deciding whether a coordination mechanism is necessary, designing an arbitrary coordination mechanism, and designing an optimal (minimal) coordination mechanism. After finding out that designing an optimal coordination mechanism is difficult, we concentrate on an algorithm that is able to find a (non-trivial) coordination mechanism that is not always minimal. We then discuss some subclasses of plan-coordination instances where this algorithm performs very badly, but also some class of instances where a nearly optimal coordination mechanism is returned. Hereafter, we discuss the price of autonomy as a measure to determine the loss of (global) performance of a system due to the use of a coordination mechanism, and we offer a case study on multi-modal transportation where a coordination mechanism can be designed that offers minimal restrictions and guarantee nearly optimal performance. We will also place the use of these coordination mechanisms in a more general perspective, claiming that they can be used to reuse existing (single) agent software in a complex multi-agent environment. Finally, we briefly discuss some recent extensions of our coordination framework dealing with temporal planning aspects.