Coalitions among computationally bounded agents
Artificial Intelligence - Special issue on economic principles of multi-agent systems
Coalition structure generation with worst case guarantees
Artificial Intelligence
Alternating-time temporal logic
Journal of the ACM (JACM)
On the logic of coalitional games
AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
A Logic of Strategic Ability Under Bounded Memory
Journal of Logic, Language and Information
A logic of games and propositional control
Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 2
Coalition structure generation in multi-agent systems with positive and negative externalities
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
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We propose Alternating-time Dynamic Logic (ADL) as a multi-agent variant of Dynamic Logic in which atomic programs are replaced by coalitions. In ADL, the Dynamic Logic operators are parametrised with regular expressions over coalitions and tests. Such regular expressions describe the dynamic structure of a coalition. This means that, when moving from Dynamic Logic to ADL, the focus shifts away from describing what is executed and when, toward describing who is acting and when. While Dynamic Logic provides for reasoning about complex programs, ADL facilitates reasoning about coalitions with an inner dynamic structure, so-called coordinated coalitions. The semantics for such coalitions involves partial strategies and a variety of ways to combine them. Different combinations of partial strategies give rise to different semantics for ADL. In this paper, we mainly focus on one version of the semantics but we provide a discussion on other semantic variants of ADL together with possible syntactic extensions. We see ADL to be suitable for the specification and the verification of scheduling and planning systems, and we therefore present a model checking algorithm for ADL and investigate its computational complexity.