In this paper, we develop a framework for path-planning on abstractions that are not provided to the system a-priori but instead emerge as a function of the agent's available computational resources. We show how a path-planning problem in an environment can be systematically approximated by solving a sequence of easier to solve problems on abstractions of the original space. The properties of the problem are analyzed, and supporting theoretical results presented and discussed. A numerical example is presented to show the utility of the approach and to corroborate the theoretical findings. We conclude by providing a discussion of the results and their interpretation relating to anytime algorithms and bounded rationality.

中文翻译：

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具有计算约束的智能体路径规划的信息论方法

在本文中，我们开发了一个抽象路径规划框架，这些抽象不是先验提供给系统的，而是作为代理可用计算资源的函数出现的。我们展示了如何通过解决一系列更容易解决的原始空间抽象问题来系统地近似环境中的路径规划问题。分析了问题的性质，并提出和讨论了支持的理论结果。给出了一个数值例子来说明该方法的实用性并证实了理论发现。最后，我们讨论了与任何时间算法和有限理性相关的结果及其解释。