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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 coali-tional ability. However, coalitional ability can be affected by the availability of resources, and there is no straightforward way of reasoning about(More)
Recent work on Alternating-Time Temporal Logic and Coalition Logic has allowed the expression of many interesting properties of coalitions and strategies. However there is no natural way of expressing resource requirements in these logics. This paper presents a Resource-Bounded Coalition Logic (RBCL) which has explicit representation of resource bounds in(More)
We present a framework for verifying systems composed of heterogeneous reasoning agents, in which each agent may have differing knowledge and inferential capabilities, and where the resources each agent is prepared to commit to a goal (time, memory and communication bandwidth) are bounded. The framework allows us to investigate, for example, whether a goal(More)
The development of many complex simulation applications requires collaborative effort from researchers with different domain knowledge and expertise, possibly at different locations. These simulation systems often require huge computing resources and data sets, which may be geographically distributed. In order to support collaborative model development and(More)