Deriving Multi-Agent Coordination through Filtering Strategies
Proceedings of the Fourteenth International Joint Conference on Artificial Intelligence. Distributed AI. Pages 679-686.
Abstract
We examine an approach to multi-agent coordination that builds on earlier work on enabling single agents to control their reasoning in dynamic environments. Specifically, we study a generalization of the filtering strategy. Where single-agent filtering means tending to bypass options that are incompatible with an agent's own goals, multi-agent filtering means tending to bypass options that are incompatible with other agents' known or presumed goals. We examine several versions of multi-agent filtering, which range from purely implicit to minimally explicit, and discuss the trade -offs among these. We also describe a series of experiments that demonstrate initial results about the feasibility of using multi-agent filtering to achieve coordination without explicit negotiation.
@inproceedings{ijcai1995p89,
title = {Deriving Multi-Agent Coordination through Filtering Strategies},
author = {Ephrati, Eithan and Pollack, Martha E. and Ur, Sigalit},
booktitle = {Proceedings of the Fourteenth International Joint Conference on
Artificial Intelligence, {IJCAI-95}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {Chris S. Mellish},
pages = {679--686},
year = {1995},
note = {Distributed AI},
url = {https://ijcai.org/proceedings/1995/89},
}
TY - CPAPER TI - Deriving Multi-Agent Coordination through Filtering Strategies AU - Ephrati, Eithan AU - Pollack, Martha E. AU - Ur, Sigalit T2 - Proceedings of the Fourteenth International Joint Conference on Artificial Intelligence, IJCAI-95 PB - International Joint Conferences on Artificial Intelligence PY - 1995 SP - 679 EP - 686 UR - https://ijcai.org/proceedings/1995/89 ER -Copied
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