A multi-agent queuing model for resource allocations in a non-cooperative game

In this paper, we investigate a multi-agent non-cooperative game for resource allocations based on an M/D/1 queuing model. Specifically, agents with common goals to maximize individual utility are deployed to compete with each other to bid or bribe for quicker service provided by the server. Agents choose from one of three available strategies: random strategy, Nash equilibrium strategy and linear regression strategy, for their decision-makings. After each agent obtained service, it re-evaluates its strategy and adjusts it accordingly. Results show that in the long run, the dominant strategy depends on the service speed. When the service speed is low, random strategy dominates the society. But if the service speed is high, linear regression strategy dominates. The model can be extended to study agent-based social simulations and decentralized scheduling for resource allocations in an open multi-agent system