Teacher:In this task, you are given a part of an article. Your task is to generate headline (title) for this text. Preferred headlines are under fifteen words.
Teacher: Now, understand the problem? Solve this instance: <lb>In multi-agent domains, an agent's action may not just change the world and the agent's knowledge and beliefs<lb>about the world, but also may change other agents' knowledge and beliefs about the world and their knowledge and<lb>beliefs about other agents' knowledge and beliefs about the world. Similarly, the goals of an agent in a multi-agent<lb>world may involve manipulating the knowledge and beliefs of other agents' and again, not just their knowledge<lb>about the world, but also their knowledge about other agents' knowledge about the world. The goal of this paper is to<lb>present an action language, called mA+, that has the necessary features to address the above aspects in representing<lb>and reasoning about actions and change in multi-agent domains.<lb>This action language can be viewed as a generalization of the single-agent action languages extensively studied<lb>in the literature, to the case of multi-agent domains. The language allows the representation of and reasoning about<lb>different types of actions that an agent can perform in a domain where many other agents might be presentsuch as<lb>world-altering actions, sensing actions, and announcement/communication actions. The action language also allows<lb>the specification of agents' dynamic awareness of action occurrences which has future implications on what agents'<lb>know about the world and other agents' knowledge about the world. The language mA+ considers three different<lb>types of awareness: full awareness, partial awareness, and complete oblivion of an action occurrence and its effects.<lb>This keeps the language simple, yet powerful enough to address a large variety of knowledge manipulation scenarios<lb>in multi-agent domains.<lb>The semantics of the language relies on the notion of state, which is described by a pointed Kripke model and<lb>is used to encode the agent's knowledge and the real state of the world. The semantics is defined by a transition<lb>function that maps pairs of actions and states into sets of states. The paper illustrates properties of the action theories,<lb>including properties that guarantee finiteness of the set of initial states and their practical implementability. Finally,<lb>the paper relates mA+ to other related formalisms that contribute to reasoning about actions in multi-agent domains.
Student:
An Action Language for Multi-Agent Domains: Foundations