Collaborative assignment using belief-desire-intention agent modeling and negotiation with speedup strategies

In this paper, we propose a distributed agent model that applies belief-desire-intention (BDI) reasoning and negotiation for addressing the linear assignment problem (LAP) collaboratively. In resource allocation, LAP is viewed as seeking a concurrent allocation of one different resource for every task to optimize a linear sum objective function. The proposed model provides a basic agent-based foundation needed for efficient resource allocation in a distributed environment. A distributed agent algorithm that has been developed based on the BDI negotiation model is examined both analytically and experimentally. To improve performance in terms of average negotiation speed and solution quality, two initialization heuristics and two different reasoning control strategies are applied, with the latter yielding different variants of the basic algorithm. Extensive simulations suggest that all the heuristic-algorithm combinations can produce a near optimal solution soon enough in some specific sense. The significance and applicability of the research work are also discussed.