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Best A* discovery for multi agents planning

机译:最佳A *发现多代理规划

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This paper proposes a new approach for multi-agent planning and decision support. The conventional algorithms such as Dijkstra, A* cannot solve complex problems with spatio-temporal constraints. So we are interested in developing a new strategy for the best path based on BDI agents for an emergency evacuation problem of a population crowd, besides the study of the macroscopic behaviour emerging from simple interactions between agents by decreasing the evacuation time which is a challenge and a very complex task. Multi-agent systems are well suited to modelling such systems. The idea is to make a two-dimensional modelling of the environment as a quadtree graph and an hybrid architecture: A* search from the node, where the individual is located to direct it to the best exit node while adding physiological factors to this research, a robust method for collision avoidance and decision support to help the agent will replace the initial destination with anew one. Our model is implemented and tested with java and Netlogo 5.2.1 platform.
机译:本文提出了一种新的多智能经纪规划和决策支持方法。诸如Dijkstra的传统算法,A *不能解决时空约束的复杂问题。因此,我们有兴趣为基于人群的紧急疏散问题的基于BDI代理商的基于BDI代理商的最佳路径开发新的策略,除了通过减少挑战的疏散时间和一个非常复杂的任务。多种代理系统非常适合于建模此类系统。这个想法是将环境的二维建模作为四叉树图和一个混合架构:从节点中的一个*搜索,其中个体所在的位置,以便将其引导到最佳出口节点,同时为这项研究添加生理因素,用于帮助该代理的碰撞避免和决策支持的强大方法将用重组替换初始目的地。我们的模型与Java和NetLogo 5.2.1平​​台实现和测试。

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