Simultaneous Localisation and Planning

W. Penny
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引用次数: 6

Abstract

This paper proposes an algorithm for the solution of the Simultaneous Localisation and Planning problem. The solution is based on statistical inference in a Hidden Markov Model which proceeds in separate phases of localisation and planning. Each requires access to the same contextual model operationalised via the `prior dynamics', and is implemented using forward (localisation) and forward and backward (planning) message passing. I propose that this formalism provides a useful computational-level description of aspects of Hippocampal function.
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同时进行本地化和规划
本文提出了一种求解同时定位和规划问题的算法。该解决方案基于隐马尔可夫模型中的统计推断,隐马尔可夫模型在定位和规划的不同阶段进行。每个都需要访问通过“先验动态”操作的相同上下文模型,并使用前向(本地化)和前向和后向(规划)消息传递实现。我认为,这种形式主义提供了一种有用的海马功能方面的计算级描述。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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