# Changing the Environment Based on Empowerment as Intrinsic Motivation

arXiv: https://arxiv.org/abs/1406.1767 · HTML: https://mlsanity.com/paper/1406.1767/

## Key facts

- Cited by 10 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 3 Jun 2014.

## Built on by (most cited first, 10 of 10)

- [Choreographer: Learning and Adapting Skills in Imagination](https://mlsanity.com/paper/2211.13350/) (2022)
- [Intrinsically-Motivated Humans and Agents in Open-World Exploration](https://mlsanity.com/paper/2503.23631/) (2025)
- [Explore and Control with Adversarial Surprise](https://mlsanity.com/paper/2107.07394/) (2021)
- [BAMDP Shaping: a Unified Framework for Intrinsic Motivation and Reward Shaping](https://mlsanity.com/paper/2409.05358/) (2024)
- [Information-Theoretic Policy Pre-Training with Empowerment](https://mlsanity.com/paper/2510.05996/) (2025)
- [Decentralized Traffic Flow Optimization Through Intrinsic Motivation](https://mlsanity.com/paper/2505.11520/) (2025)
- [Artificial Agency Program: Curiosity, compression, and communication in agents](https://mlsanity.com/paper/2602.24100/) (2026)
- [Credit Assignment and Efficient Exploration based on Influence Scope in Multi-agent Reinforcement Learning](https://mlsanity.com/paper/2505.08630/) (2025)
- [C-STEP: Continuous Space-Time Empowerment for Physics-informed Safe Reinforcement Learning of Mobile Agents](https://mlsanity.com/paper/2603.24241/) (2026)
- [Scaling Empowered Agents](https://mlsanity.com/paper/2610.13002/) (2026)

## Abstract (arXiv)

One aspect of intelligence is the ability to restructure your own environment so that the world you live in becomes more beneficial to you. In this paper we investigate how the information-theoretic measure of agent empowerment can provide a task-independent, intrinsic motivation to restructure the world. We show how changes in embodiment and in the environment change the resulting behaviour of the agent and the artefacts left in the world. For this purpose, we introduce an approximation of the established empowerment formalism based on sparse sampling, which is simpler and significantly faster to compute for deterministic dynamics. Sparse sampling also introduces a degree of randomness into the decision making process, which turns out to beneficial for some cases. We then utilize the measure to generate agent behaviour for different agent embodiments in a Minecraft-inspired three dimensional block world. The paradigmatic results demonstrate that empowerment can be used as a suitable generic intrinsic motivation to not only generate actions in given static environments, as shown in the past, but also to modify existing environmental conditions. In doing so, the emerging strategies to modify an agent's environment turn out to be meaningful to the specific agent capabilities, i.e., de facto to its embodiment.