A Scheme for Agent Collaboration in Open Multiagent Environments
Proceedings of the Thirteenth International Joint Conference on Artificial Intelligence. Distributed AI. Pages 352-358.
Abstract
In multiagent planning, a.n agent sometimes needs to collaborate with others to construct complex plans, or to accomplish large organizational tasks which it cannot do alone. Since each agent in a group may have incorrect beliefs about the world and incomplete knowledge, and because agent's abilities differ, constructing a coordinated collaborative plan among agents is a difficult proposition. In previous work [Osawa and Tokoro 92], we developed a scheme for constructing collaborative plans from the, possibly incomplete, individual plans of agents. This scheme was designed to provide availability-based assignment of goals to agents, and opportunistic collaboration to distributed planning in open multiagent environments based on the contract net. In this paper, we formalize incomplete individual plans and collaborative planning among rational agents using the Multi-World Model, and provide a utility-based model for rational choice of actions. Agents can effectively balance workloads based on the utility theory. A condition for incomplete collaborative plans is also presented.
@inproceedings{ijcai1993p50,
title = {A Scheme for Agent Collaboration in Open Multiagent Environments},
author = {Osawa, Eiichi},
booktitle = {Proceedings of the Thirteenth International Joint Conference on
Artificial Intelligence, {IJCAI-93}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {Ruzena Bajcsy},
pages = {352--358},
year = {1993},
note = {Distributed AI},
url = {https://ijcai.org/proceedings/1993/50},
}
TY - CPAPER TI - A Scheme for Agent Collaboration in Open Multiagent Environments AU - Osawa, Eiichi T2 - Proceedings of the Thirteenth International Joint Conference on Artificial Intelligence, IJCAI-93 PB - International Joint Conferences on Artificial Intelligence PY - 1993 SP - 352 EP - 358 UR - https://ijcai.org/proceedings/1993/50 ER -Copied
Machine-readable versions of this paper, for tools and AI agents: