# The Evolution theory of Learning: From Natural Selection to Reinforcement Learning

arXiv: https://arxiv.org/abs/2306.09961 · HTML: https://mlsanity.com/paper/2306.09961/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 1 of its 29 references that are in the map.
- First posted on arXiv 16 Jun 2023.

## Builds on (most cited first, 1 of 1)

- [Robots that can adapt like animals](https://mlsanity.com/paper/1407.3501/) (2014)

## Abstract (arXiv)

Evolution is a fundamental process that shapes the biological world we inhabit, and reinforcement learning is a powerful tool used in artificial intelligence to develop intelligent agents that learn from their environment. In recent years, researchers have explored the connections between these two seemingly distinct fields, and have found compelling evidence that they are more closely related than previously thought. This paper examines these connections and their implications, highlighting the potential for reinforcement learning principles to enhance our understanding of evolution and the role of feedback in evolutionary systems.