Abstract
Many problems in AI and multi-agent systems research are most naturally formulated in terms of the abilities of a coalition of agents. There exist several excellent logical tools for reasoning about coalitional ability. However, coalitional ability can be affected by the availability of resources, and there is no straightforward way of reasoning about resource requirements in logics such as Coalition Logic (CL) and Alternating-time Temporal Logic (ATL). In this article, we describe a logic for reasoning about coalitional ability under resource constraints. We extend ATL with costs of actions and hence of strategies. We give a complete and sound axiomatization of the resulting logic, Resource-Bounded ATL (RB-ATL) and a model-checking algorithm for it.
Highlights
In many situations, a group of agents can cooperate to achieve an outcome which cannot be achieved by any agent in the group acting individually
We studied a version of Coalition Logic with resource bounds, RBCL [5]
We describe a model-checking algorithm for RB-Alternating-time Temporal Logic (ATL) which runs in time polynomial in the size of the formula and the structure, and is exponential in the number of resources
Summary
A group of agents can cooperate to achieve an outcome which cannot be achieved by any agent in the group acting individually. In the prisoners dilemma, a single prisoner cannot ensure the optimal outcome, while a coalition of two prisoners can It may be possible for a set of cooperating agents to solve a difficult computational problem by distributing it, while a single agent may not have sufficient memory or processor power to solve it. We studied a version of Coalition Logic with resource bounds, RBCL [5]. In [4], we gave a sound and complete axiomatisation and a model-checking algorithm for a version of RB-ATL without infinite resource bounds.
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