Author : Benjamin Wright
Publisher :
ISBN 13 :
Total Pages : 274 pages
Book Rating : 4.:/5 (11 download)
Book Synopsis Doxastic Attitudes for Reasoning Over Multi-agent Domains by : Benjamin Wright
Download or read book Doxastic Attitudes for Reasoning Over Multi-agent Domains written by Benjamin Wright and published by . This book was released on 2018 with total page 274 pages. Available in PDF, EPUB and Kindle. Book excerpt: Epistemic reasoning entails the ability of an agent to reason about the knowledge and beliefs of any agents within a multi-agent systems. In the context of reasoning and acting in a multi-agent epistemic domain, it is not uncommon to have agents end up having false beliefs, or beliefs that are in conflict with the real world. This aspect however, has not been properly illustrated in the context of multi-agent epistemic planning. Using a modified version of the action language mA+, we explore two examples that have false belief, the Light Room and the Prison Escapee examples, and give implementation designs in the Picat logic programming framework to solve them. These implementations both run in reasonable time and are modifiable enough to reason about the beliefs of any agent, at any action step. In recent years, we have witnessed a blossoming of research proposals addressing the challenges in reasoning about action and change in domains that include an agent operating in a multi-agent setting. In particular, the recent emphasis has been on dealing with domains that involve agents reasoning not only about the state of the world about also about the knowledge and beliefs of other agents. An open challenge is the management of conflicting and incorrect beliefs. We introduce a solution to this through the use of doxastic attitudes. Built on top of the action language mA+, we extend the transition functions of an agent to include this idea of attitudes and showcase how these work in two different examples, Light Room and Prison Escapee. Using the Light Room and Prison Escapee examples as reference points, we formalize the implementation of reasoning with attitudes using Picat. Since our attitudes and actions are based on the modified mA+ action language, we showcase how the different action types are represented in Picat and their connection to their transition functions. These transitions follow closely the similar implementations of other action languages.