Qualitative coalitional games (QCGs) were introduced as abstract formal models of goal-oriented cooperative systems. A QCG is a game in which each agent is assumed to have some goal to achieve, and in which agents must typically cooperate with others in order to satisfy their goals. In this paper, we show how it is possible to reason about QCGs using Coalition Logic (CL), a formalism intended to facilitate reasoning about coalitional powers in game-like multiagent systems. We introduce a correspondence relation (...) between QCGs and interpretations for CL, which defines the circumstances under which a CL interpretation correctly characterises a QCG. The complexity of deciding correspondence between QCGs and interpretations for CL is shown to vary from being tractable up to Πp 2-complete, depending on the representation chosen for the QCG and interpretation. We then show how various properties and solution concepts of QCGs can be characterised as CL formula schemes. The ideas are illustrated via a detailed worked example, in which we demonstrate how a model checker can be deployed to investigate whether a particular system has the properties in question. (shrink)

In this paper, a logic for reasoning about coalitional power is developed which explicitly represents agents’ preferences and the actions by which the agents can achieve certain results. A complete axiomatization is given and its satisfiability problem is shown to be decidable and EXPTIME -hard.

The aim of this paper, is to provide a logical framework for reasoning about actions, agency, and powers of agents and coalitions in game-like multi-agent systems. First we define our basic Dynamic Logic of Agency ( ). Differently from other logics of individual and coalitional capability such as Alternating-time Temporal Logic (ATL) and Coalition Logic, in cooperation modalities for expressing powers of agents and coalitions are not primitive, but are defined from more basic dynamic logic operators of action and (historic) (...) necessity. We show that STIT logic can be reconstructed in . We then extend with epistemic operators, which allows us to distinguish capability and power. We finally characterize the conditions under which agents are aware of their capabilities and powers. (shrink)