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CLC number: TP182
On-line Access: 2024-08-27
Received: 2023-10-17
Revision Accepted: 2024-05-08
Crosschecked: 2016-12-29
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Coalition formation based on a task-oriented collaborative ability vector
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Hao Fang, Shao-lei Lu, Jie Chen, Wen-jie Chen. Coalition formation based on a task-oriented collaborative ability vector[J]. Frontiers of Information Technology & Electronic Engineering, 2017, 18(1): 139-148.
@article{title="Coalition formation based on a task-oriented collaborative ability vector",
author="Hao Fang, Shao-lei Lu, Jie Chen, Wen-jie Chen",
journal="Frontiers of Information Technology & Electronic Engineering",
volume="18",
number="1",
pages="139-148",
year="2017",
publisher="Zhejiang University Press & Springer",
doi="10.1631/FITEE.1601608"
}
%0 Journal Article
%T Coalition formation based on a task-oriented collaborative ability vector
%A Hao Fang
%A Shao-lei Lu
%A Jie Chen
%A Wen-jie Chen
%J Frontiers of Information Technology & Electronic Engineering
%V 18
%N 1
%P 139-148
%@ 2095-9184
%D 2017
%I Zhejiang University Press & Springer
%DOI 10.1631/FITEE.1601608
TY - JOUR
T1 - Coalition formation based on a task-oriented collaborative ability vector
A1 - Hao Fang
A1 - Shao-lei Lu
A1 - Jie Chen
A1 - Wen-jie Chen
J0 - Frontiers of Information Technology & Electronic Engineering
VL - 18
IS - 1
SP - 139
EP - 148
%@ 2095-9184
Y1 - 2017
PB - Zhejiang University Press & Springer
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DOI - 10.1631/FITEE.1601608
Abstract: coalition formation is an important coordination problem in multi-agent systems, and a proper description of collaborative abilities for agents is the basic and key precondition in handling this problem. In this paper, a model of task-oriented collaborative abilities is established, where five task-oriented abilities are extracted to form a collaborative ability vector. A task demand vector is also described. In addition, a method of coalition formation with stochastic mechanism is proposed to reduce excessive competitions. An artificial intelligent algorithm is proposed to compensate for the difference between the expected and actual task requirements, which could improve the cognitive capabilities of agents for human commands. Simulations show the effectiveness of the proposed model and the distributed artificial intelligent algorithm.
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