# Information-Theoretic Abstractions for Planning in Agents with Computational Constraints

arXiv: https://arxiv.org/abs/2005.09611 · HTML: https://mlsanity.com/paper/2005.09611/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 19 May 2020.

## Built on by (most cited first, 3 of 3)

- [A Linear Programming Approach for Resource-Aware Information-Theoretic Tree Abstractions](https://mlsanity.com/paper/2208.04220/) (2022)
- [Communication-aware Hierarchical Map Compression of Time-Varying Environments for Mobile Robots](https://mlsanity.com/paper/2504.10751/) (2025)
- [Efficient Hierarchical Any-Angle Path Planning on Multi-Resolution 3D Grids](https://mlsanity.com/paper/2602.21174/) (2026)

## Abstract (arXiv)

In this paper, we develop a framework for path-planning on abstractions that are not provided to the agent a priori but instead emerge as a function of the 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 a number of theoretical results are 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 detailing the connections of the proposed approach to anytime algorithms and bounded rationality.