Title
An action language for multi-agent domains
Abstract
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.
Year
DOI
Venue
2022
10.1016/j.artint.2021.103601
Artificial Intelligence
Keywords
DocType
Volume
Action languages,Epistemic planning,Reasoning about knowledge
Journal
302
Issue
ISSN
Citations 
1
0004-3702
0
PageRank 
References 
Authors
0.34
0
4
Name
Order
Citations
PageRank
Chitta Baral12353269.58
Gregory Gelfond2243.97
Enrico Pontelli31901181.26
Tran Cao Son41795169.42