Abstract: This paper addresses the challenge of learning to play many different video games with little domain-specific knowledge. Specifically, it introduces a neuroevolution approach to general ...

Neuroevolution with multiple objectives allows for populations of agents to evolve different solutions based on various trade-offs inherent in any given domain. In particular, these methods can be ...

Neuroevolution is the discipline whereby ANNs are automatically generated using EC. This field began with the evolution of dense (shallow) neural networks for reinforcement learning task; ...

Abstract: This paper uses neuroevolution of augmenting topologies to evolve control tactics for groups of units in real-time strategy games. In such games, players build economies to generate armies ...

This project explores how simple genetic algorithms can be used to solve reinforcement learning environments by evolving neural networks, completely bypassing traditional gradient-based methods like ...

The textbook for this class is Risi, Tang, Ha, and Miikkulainen (2025): Neuroevolution: Harnessing Creativity in AI Model Design Cambridge, MA: MIT Press. For reference, here are pointers to the ...

This project explores how simple genetic algorithms can be used to solve reinforcement learning environments by evolving neural networks, completely bypassing traditional gradient-based methods like ...