TY - JOUR
T1 - MALLET - A Multi-Agent Logic Language for Encoding Teamwork
AU - Fan, Xiaocong
AU - Yen, John
AU - Miller, Michael
AU - Ioerger, Thomas R.
AU - Volz, Richard
N1 - Funding Information:
This research has been supported by AFOSR MURI grant No. F49620-00-1-0326. The authors would like to thank Dianxiang Xu at North Dakota State University, Rui Wang at Pennsylvania State University, and Sen Cao and Ryan Rozich at Texas A&M University for their contributions in evolving the MALLET language. This is a significant extension of a workshop paper published in the Lecture Notes of Artificial Intelligence (Springer). Certain materials are reprinted from [1] with the kind permission of Springer Science and Business Media.
PY - 2006/1
Y1 - 2006/1
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=31344460369&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=31344460369&partnerID=8YFLogxK
U2 - 10.1109/TKDE.2006.13
DO - 10.1109/TKDE.2006.13
M3 - Article
AN - SCOPUS:31344460369
SN - 1041-4347
VL - 18
SP - 123
EP - 138
JO - IEEE Transactions on Knowledge and Data Engineering
JF - IEEE Transactions on Knowledge and Data Engineering
IS - 1
ER -