%0 Journal Article
%A Yan Fengting
%A Jia Jinyuan
%T DP-Q(*λ*): Real-time Path Planning for Multi-agent in Large-scale Web3D Scene
%D 2019
%R 10.16182/j.issn1004731x.joss.16PQS-003
%J Journal of System Simulation
%P 16-26
%V 31
%N 1
%X The path planning of multi-agent in an unknown large-scale scene needs an efficient and stable algorithm, and needs to solve multi-agent collision avoidance problem, and then completes a real-time path planning in Web3D. To solve above problems,* the DP-Q(λ) algorithm is proposed; and the direction constraints, high reward or punishment weight training methods are used to adjust the values of reward or punishment by using a probability p (0-1 random number). The value from reward or punishment determines its next step path planning strategy. *If the next position is free, the agent could walk to it. *The above strategy is extended to multi-agent path planning, and is used in Web3D.* The experiment shows that the DP-Q(*λ*) algorithm is efficient and stable in the Web3D real-time multi-agent path planning.
%U https://www.china-simulation.com/EN/10.16182/j.issn1004731x.joss.16PQS-003