The Use of Meta-level Information in Learning Situation-Specific Coordination
Proceedings of the Fifteenth International Joint Conference on Artificial Intelligence. Distributed Artificial Intelligence. Pages 640-645.
Abstract
Achieving effective cooperation in a multi-agent system is a difficult problem for a number of reasons such as limited and possibly out-dated views of activities of other agents and uncertainty about the outcomes of interacting non-local tasks. In this paper, we present a learning algorithm that endows agents with the capability to choose the appropriate coordination algorithm from a set of available coordination algorithms based on meta-level information about their problem solving situations. We present empirical results that strongly indicate the effectiveness of the learning algorithm.
@inproceedings{ijcai1997p94,
title = {The Use of Meta-level Information in Learning Situation-Specific Coordination},
author = {Prasad, M. V. Nagendra and Lesser, Victor R.},
booktitle = {Proceedings of the Fifteenth International Joint Conference on
Artificial Intelligence, {IJCAI-97}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {Martha E. Pollack},
pages = {640--645},
year = {1997},
note = {Distributed Artificial Intelligence},
url = {https://ijcai.org/proceedings/1997/94},
}
TY - CPAPER TI - The Use of Meta-level Information in Learning Situation-Specific Coordination AU - Prasad, M. V. Nagendra AU - Lesser, Victor R. T2 - Proceedings of the Fifteenth International Joint Conference on Artificial Intelligence, IJCAI-97 PB - International Joint Conferences on Artificial Intelligence PY - 1997 SP - 640 EP - 645 UR - https://ijcai.org/proceedings/1997/94 ER -Copied
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