Gautier Hamon, Eleni Nisioti, and Clément Moulin-Frier. ‘Eco-Evolutionary Dynamics of Non-Episodic Neuroevolution in Large Multi-Agent Environments’. arXiv, 18 February 2023.


Short description: Learning foraging strategies using neuroevolution in a JAX grid-world with thousands of agents and spatiotemporal variability in resources.

Elías Masquil, Gautier Hamon, Eleni Nisioti, and Clément Moulin-Frier. ‘Intrinsically-Motivated Goal-Conditioned Reinforcement Learning in Multi-Agent Environments’. arXiv, 11 November 2022.


Short description: How can a group of agents learn to solve a diversity of cooperative tasks without supervision? We show that aligning goals is a good strategy and design an emergent-communicaiton algorithm to achieve it.

Eleni Nisioti, Mateo Mahaut, Pierre-Yves Oudeyer, Ida Momennejad, and Clément Moulin-Frier. ‘Social Network Structure Shapes Innovation: Experience-Sharing in RL with SAPIENS’. arXiv, 18 November 2022.


Short description: Reinforcement learning agents play the Little Alchemy 2 game. Will sharing experiences help them and who should they share with?

Eleni Nisioti, Clément Moulin-Frier. “Plasticity and evolvability under environmental variability: the joint role of fitness-based selection and niche-limited competition”, GECCO, July 2022, Boston


Short description: What are the costs and benefits of plasticity in variable environments? We explore questions about the emergence of adaptability through a simple eco-evolutionary model.

Eleni Nisioti and Katia Jodogne-del Litto and Clément Moulin-Frier, “Grounding an Ecological Theory of Artificial Intelligence in Human Evolution”, NeurIPS 2021- Conference on Neural Information Processing Systems / Workshop: Ecological Theory of Reinforcement Learning, Dec 2021

Short description: How can ecologists and AI researchers communicate about their study of skill acquisition in natural and artificial ecosystems? A conceptula framework for bridging the gap