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In this paper we present a decentralised algorithm to solve the Task Allocation problem. Given a set of tasks and a set of robots each with its own utility function, this problem concerns the non-overlapping allocation of tasks to agents maximising the sum of the robot's utility functions. Our algorithm provides a constant factor approximation of (1 − 1/e ≈ 63%) for positive-valued monotone submodular...
This paper proposes a framework for decentralised task allocation in which agents find a global solution sharing local performance metrics. Leveraging the PAUSE procedure for Combinatorial Auctions we outline a decentralised version of in order to solve a task allocation problem. The algorithm has polynomial communications overheads and it can also accommodate a variety of objective functions and...
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