Research on Resource Allocation Strategy of Swarm Robot Based on Historical Information

Abstract

To solve the communication resource allocation problem of swarm robots in emergency rescue scenarios, an evolutionary game-based resource allocation strategy is proposed. The complex dynamic equation of the evolutionary game is constructed through the payoff function, cost function and utility function of the resource consumption robot. The monotonicity of the replication dynamic equation is proved and the evolutionary game equilibrium solution is obtained. For the time-varying characteristics of emergency scenarios, the evolutionary game model is optimized by introducing historical information conditions within the memory length in the evolution of replication dynamic equations. By simulation, the proposed evolutionary game model is evaluated. The results show that the distribution of the population tends to converge and exists stably after 25 iterations. By comparing the historical average income information with the current income information under different memory lengths, it is found that the convergence speed is the fastest and the convergence is the best when the medium memory length m=5.