Divide and conquer in multi-agent planning
AAAI '94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 1)
Fast planning through planning graph analysis
Artificial Intelligence
An efficient algorithm for multiagent plan coordination
Proceedings of the fourth international joint conference on Autonomous agents and multiagent systems
Partial-order planning with concurrent interacting actions
Journal of Artificial Intelligence Research
Distributed AI for ambient intelligence: issues and approaches
AmI'07 Proceedings of the 2007 European conference on Ambient intelligence
Planning for multiagent using ASP-prolog
CLIMA'09 Proceedings of the 10th international conference on Computational logic in multi-agent systems
µ-SATPLAN: Multi-agent planning as satisfiability
Knowledge-Based Systems
Reasoning and planning with cooperative actions for multiagents using answer set programming
DALT'09 Proceedings of the 7th international conference on Declarative Agent Languages and Technologies
Generating project plans for data center transformations
AI'12 Proceedings of the 25th Australasian joint conference on Advances in Artificial Intelligence
| Hi-index | 0.01 |
Multi-agent planning is a fundamental problem in multi-agent systems that has acquired a variety of meanings in the relative literature. In this paper we focus on a setting where multiple agents with complementary capabilities cooperate in order to generate non-conflicting plans that achieve their respective goals. We study two situations. In the first, the agents are able to achieve their subgoals by themselves, but they need to find a coordinated course of action that avoids harmful interactions. In the second situation, some agents may ask the assistance of others in order to achieve their goals. We formalize the two problems and present algorithms for their solution. These algorithms are based on an underlying classical planner which is used by the agents to generate their individual plans, but also to find plans that are consistent with those of the other agents. The procedures generate optimal plans under the plan length criterion. The central role that has been given to the classical planning algorithm, can be seen as an attempt to establish a stronger link between classical and multi-agent planning.