Biological neural networks are systems of extraordinary computational capabilities shaped
by evolution, development, and lifelong learning. The interplay of these elements leads to …

Autonomous agents have made great strides in specialist domains like Atari games and Go.
However, they typically learn tabula rasa in isolated environments with limited and manually …

This article provides an overview of evolutionary robotics techniques applied to online
distributed evolution for robot collectives, namely, embodied evolution. It provides a …

This chapter pursues the insight that large language models (LLMs) trained to generate
code can vastly improve the effectiveness of mutation operators applied to programs in …

While the history of machine learning so far largely encompasses a series of problems
posed by researchers and algorithms that learn their solutions, an important question is …

Zero-sum games such as chess and poker are, abstractly, functions that evaluate pairs of
agents, for example labeling them 'winner'and 'loser'. If the game is approximately transitive …

Creating open-ended algorithms, which generate their own never-ending stream of novel
and appropriately challenging learning opportunities, could help to automate and accelerate …

Perhaps the most ambitious scientific quest in human history is the creation of general
artificial intelligence, which roughly means AI that is as smart or smarter than humans. The …

Behavioral genetics and cultural evolution have both revolutionized our understanding of
human behavior–largely independent of each other. Here, we reconcile these two fields …

How can progress in machine learning and reinforcement learning be automated to
generate its own never-ending curriculum of challenges without human intervention? The …