An action language for multi-agent domains

The goal of this paper is to investigate an action language, called mA^⁎, for representing and reasoning about actions and change in multi-agent domains. The language, as designed, can also serve as a specification language for epistemic planning, thereby addressing an important issue in the development of multi-agent epistemic planning systems. The mA^⁎ action language is a generalization of the single-agent action languages, extensively studied in the literature, to the case of multi-agent domains. The language allows the representation of different types of actions that an agent can perform in a domain where many other agents might be present—such as world-altering actions, sensing actions, and communication actions. The action language also allows the specification of agents' dynamic awareness of action occurrences—which has implications on what agents' know about the world and other agents' knowledge about the world. These features are embedded in a language that is simple, yet powerful enough to address a large variety of knowledge manipulation scenarios in multi-agent domains. The semantics of mA^⁎ relies on the notion of state, which is described by a pointed Kripke model and is used to encode the agents' knowledge¹ and the real state of the world. The semantics is defined by a transition function that maps pairs of actions and states into sets of states. The paper presents a number of properties of the action theories and relates mA^⁎ to other relevant formalisms in the area of reasoning about actions in multi-agent domains.