학술논문

MALLET - a multi-agent logic language for encoding teamwork
Document Type
Periodical
Source
IEEE Transactions on Knowledge and Data Engineering IEEE Trans. Knowl. Data Eng. Knowledge and Data Engineering, IEEE Transactions on. 18(1):123-138 Jan, 2006
Subject
Computing and Processing
Encoding
Teamwork
Humans
Artificial intelligence
Intelligent agent
Collaboration
Logic programming
Intelligent structures
Problem-solving
Java
Index Terms- Artificial intelligence
distributed artificial intelligence
languages and structures.
Language
ISSN
1041-4347
1558-2191
2326-3865
Abstract
MALLET, a multi-agent logic language for encoding teamwork, is intended to enable expression of teamwork emulating human teamwork, allowing experimentation with different levels and forms of inferred team intelligence. A consequence of this goal is that the actual teamwork behavior is determined by the level of intelligence built into the underlying system as well as the semantics of the language. In this paper, we give the design objectives, the syntax, and an operational semantics for MALLET in terms of a transition system. We show how the semantics can be used to reason about the behaviors of team-based agents. The semantics can also be used to guide the implementation of various MALLET interpreters emulating different forms of team intelligence, as well as formally study the properties of team-based agents specified in MALLET. We have explored various forms of proactive information exchange behavior embodied in human teamwork using the CAST system, which implements a built-in MALLET interpreter.