All I know: a study in autoepistemic logic
Artificial Intelligence
Reasoning about knowledge
Modal logic
Dynamic Epistemic Logic
Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 1
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Knowing more: from global to local correspondence
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
On the measure of conflicts: Shapley Inconsistency Values
Artificial Intelligence
On the synthesis of useful social laws for artificial agent societies
AAAI'92 Proceedings of the tenth national conference on Artificial intelligence
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In epistemic logic, Kripke structures are used to model the distribution of information in a multi-agent system. In this paper, we present an approach to quantifying how much information each particular agent in a system has, or how important the agent is, with respect to some fact represented as a goal formula. It is typically the case that the goal formula is distributed knowledge in the system, but that no individual agent alone knows it. It might be that several different groups of agents can get to know the goal formula together by combining their individual knowledge. By using power indices developed in voting theory, such as the Banzhaf index, we get a measure of how important an agent is in such groups. We analyse the properties of this notion of information-based power in detail, and characterise the corresponding class of voting games. Although we mainly focus on distributed knowledge, we also look at variants of this analysis using other notions of group knowledge. An advantage of our framework is that power indices and other power properties can be expressed in standard epistemic logic. This allows, e.g., standard model checkers to be used to quantitatively analyse the distribution of information in a given Kripke structure.