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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.
Index Terms- Artificial intelligence, distributed artificial intelligence, languages and structures.
Michael Miller, Xiaocong Fan, John Yen, Thomas R. Ioerger, Richard Volz, "MALLET-A Multi-Agent Logic Language for Encoding Teamwork", IEEE Transactions on Knowledge & Data Engineering, vol. 18, no. , pp. 123-138, January 2006, doi:10.1109/TKDE.2006.13
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