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A real-time decentralized algorithm for task scheduling in multi-agent system with continuous damage
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DOI：10.1016/j.asoc.2019.105628.png)
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Abstract
En 中文
In this paper, a common model of task scheduling problems in agent rescue scenario is proposed, in which tasks with continuous dynamic damage are introduced to capture the emerging applications of using rescue robots and other resources to enhance human disaster rescue capability. Beyond this, we mainly focus on finding the optimal task scheduling strategy. We design a heuristic algorithm based on greedy strategy to obtain the optimal dynamic scheduling strategy of agents. Compared with solving global integer programming directly, the computational time is greatly reduced. The proof of the greedy strategy's validity is also demonstrated under some specific damage functions. By comparing with the two strategies commonly used in real life, it is proved that our strategy is optimal. For practical application, we design an automatic negotiation framework, which realizes the real-time decentralized automated negotiation of agents. Then, using Game Description Language (GDL) as a tool, an automated negotiation algorithm is implemented, which enables agents to adjust the plan dispersedly. Experiments show that the algorithm is more efficient than the centralized algorithm in the case of limited communication. (C) 2019 Elsevier B.V. All rights reserved.
Keywords:
Task scheduling
Automated negotiation
Greedy strategy
Distributed artificial intelligence
General game playing
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