On the Formal Semantics of Speech-Act Based Communication in an Agent-Oriented Programming Language

Vieira, Renata; Moreira, Alvaro; Wooldridge, Michael; Bordini, Rafael H.

Abstract

Research on agent communication languages has typically taken the speech acts paradigm as its starting point. Despite their manifest attractions, speech-act models of communication have several serious disadvantages as a foundation for communication in artificial agent systems. In particular, it has proved to be extremely difficult to give a satisfactory semantics to speech-act based agent communication languages. In part, the problem is that speech-act semantics typically make reference to the "mental states" of agents (their beliefs, desires, and intentions), and there is in general no way to attribute such attitudes to arbitrary computational agents. In addition, agent programming languages have only had their semantics formalised for abstract, stand-alone versions, neglecting aspects such as communication primitives. With respect to communication, implemented agent programming languages have tended to be rather ad hoc. This paper addresses both of these problems, by giving semantics to speech-act based messages received by an AgentSpeak agent. AgentSpeak is a logic-based agent programming language which incorporates the main features of the PRS model of reactive planning systems. The paper builds upon a structural operational semantics to AgentSpeak that we developed in previous work. The main contributions of this paper are as follows: an extension of our earlier work on the theoretical foundations of AgentSpeak interpreters; a computationally grounded semantics for (the core) performatives used in speech-act based agent communication languages; and a well-defined extension of AgentSpeak that supports agent communication.

Citation

Vieira, R., Moreira, A., Wooldridge, M., & Bordini, R. H. (2007). On the Formal Semantics of Speech-Act Based Communication in an Agent-Oriented Programming Language. Journal of Artificial Intelligence Research, 29, 221-267

• Journal Article Type: Article
• Publication Date: Jun 1, 2007
• Deposit Date: Jul 19, 2007
• Publicly Available Date: Feb 3, 2010
• Journal: Journal of Artificial Intelligence Research
• Print ISSN: 1076-9757
• Electronic ISSN: 1943-5037
• Publisher: AI Access Foundation
• Peer Reviewed: Peer Reviewed
• Volume: 29
• Pages: 221-267
• Public URL: https://durham-repository.worktribe.com/output/1539758
• Publisher URL: http://www.jair.org/papers/paper2221.html