An Approach to Analyzing the Need for Meta-Level Communication
Proceedings of the Thirteenth International Joint Conference on Artificial Intelligence. Distributed AI. Pages 360-365.
Abstract
This paper presents an analysis of static and dynamic organizational structures for naturally distributed, homogeneous, cooperative problem solving environments, exemplified by distributed sensor networks. We first show how the performance of any static organization can be statistically described, and then show under what conditions dynamic organizations do better and worse than static ones. Finally, we show how the variance in the agents' performance leads to uncertainty about whether a dynamic organization will perform better than a static one given only agent a priori expectations. In these cases, we show when meta-level communication about the actual state of problem solving will be useful to agents in constructing a dynamic organizational structure that outperforms a static one. Viewed in its entirety, this paper also presents a methodology for answering questions about the design of distributed problem solving systems by analysis and simulation of the characteristics of a complex environment rather than by relying on single-instance examples.
@inproceedings{ijcai1993p51,
title = {An Approach to Analyzing the Need for Meta-Level Communication},
author = {Decker, Keith and Lesser, Victor R.},
booktitle = {Proceedings of the Thirteenth International Joint Conference on
Artificial Intelligence, {IJCAI-93}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {Ruzena Bajcsy},
pages = {360--365},
year = {1993},
note = {Distributed AI},
url = {https://ijcai.org/proceedings/1993/51},
}
TY - CPAPER TI - An Approach to Analyzing the Need for Meta-Level Communication AU - Decker, Keith AU - Lesser, Victor R. T2 - Proceedings of the Thirteenth International Joint Conference on Artificial Intelligence, IJCAI-93 PB - International Joint Conferences on Artificial Intelligence PY - 1993 SP - 360 EP - 365 UR - https://ijcai.org/proceedings/1993/51 ER -Copied
Machine-readable versions of this paper, for tools and AI agents: