Abstract
This article presents a novel market-based mechanism for a dynamic coalition formation problem backgrounded under real-time task allocation. Specifically, we first analyze the main factors of the real-time task allocation problem, and formulate the problem based on the coalition game theory. Then, we employ a social network for communication among distributed agents in this problem, and propose a negotiation mechanism for agents forming coalitions on timely emerging tasks. In this mechanism, we utilize an auction algorithm for real-time agent assignment on coalitions, and then design a mutual-selecting method to acquire better performance on agent utilization rate and task completion rate. And finally, our experimental results demonstrate that our market-based mechanism has a comparable performance in task completion rate to a decentralized approach (within 25% better on average) and a centralized dynamic coalition formation method (within 10% less on average performance).
Highlights
Since distributed multi-agent systems (DMASs) have been increasingly employed in real-world problems, such as disaster rescue,[1] sensor surveillance,[2] military operations,[1,3,4] and wireless sensor networks,[5,6,7] tasks with heterogeneous requirements usually emerge dynamically in those applications and need agents to cooperate to meet those requirements for successful execution
Centralized approaches are not feasible or reliable in those systems because in such a DMAS each agent needs to move to the task location when assigned a task, which means the network between the central distributor and other agents is not guaranteed to always work well.[8,9]
We propose a market-based mutual-selecting algorithm for agent dynamic coalition formation (DCF), which supports individual agents to make decisions based on local information and provides resource optimization in forming coalitions
Summary
Since distributed multi-agent systems (DMASs) have been increasingly employed in real-world problems, such as disaster rescue,[1] sensor surveillance,[2] military operations,[1,3,4] and wireless sensor networks,[5,6,7] tasks with heterogeneous requirements usually emerge dynamically in those applications and need agents to cooperate to meet those requirements for successful execution. Centralized approaches are not feasible or reliable in those systems because in such a DMAS each agent needs to move to the task location when assigned a task, which means the network between the central distributor and other agents is not guaranteed to always work well.[8,9] To deal with this issue, we focus on the use of a distributed
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