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Solving large scale block stacking problem: a distributed approach

机译:解决大规模块堆叠问题:分布式方法

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A distributed approach to large scale block stacking problem is shown, A block is assumed to be an autonomous agent which transmit messages of motion request and activates with each other. Conflicts among agent motions are resolved according to motivation value calculated considering agent's goal dependency, goal position occupation, and mobility. An activated agent determines its destination accoridng to outputs of ANN based behavior function trained using Evolutionary Programming technique. Experimental results show applicability and scalability of the approach up to the case of 200 blocks.
机译:示出了大规模块堆叠问题的分布式方法,假设块是自主代理,其发送运动请求的消息并彼此激活。根据考虑代理人的目标依赖,目标职位职业和移动性的动机价值来解决代理运动的冲突。激活的代理将其目的地accoridng与使用进化编程技术训练的基于ANN的行为函数的输出。实验结果表明,该方法的适用性和可扩展性最多为200个街区的情况。

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