8 citations · 19 across the 17 of their papers we have counts for
19 papers
Application of curiosity driven exploration methods for hardware interference identification
Ludovic Matar, Clement Moulin-Frier, Pierre-Yves Oudeyer +2
The transition from single-core to multi-core architectures in safety-critical embedded systems introduces significant challenges due to inter-core interference caused by contentio…
The Artificial Experimentalist: Discovery and Control of Self-Organizing Phenomena with Autotelic Reinforcement Learning
Marko Cvjetko, Benedikt Hartl, Michael Levin +2
Existing methods for exploring cellular automata and other complex systems mostly operate in open loop: they set initial conditions, execute a full simulation, and observe the outc…
Discovering Adaptive Transmission Programs for Collective Innovation
Cédric Colas, Jérémy Perez, Eleni Nisioti +4
Human collective intelligence depends on transmission processes: who shares what with whom, how, and when. While these processes emerge from individual cognition, they can also be…
Emergence of agriculture in an artificial society of reinforcement learning agents
Gautier Hamon, Martí Sánchez-Fibla, Clément Moulin-Frier +1
The origin of agriculture represents a major evolutionary transition and a paradigmatic example of how complex collective behaviors emerge from simple interactions. Here we introdu…
Software Engineering Agents for Embodied Controller Generation : A Study in Minigrid Environments
Timothé Boulet, Xavier Hinaut, Clément Moulin-Frier
Software Engineering Agents (SWE-Agents) have proven effective for traditional software engineering tasks with accessible codebases, but their performance for embodied tasks requir…
Complex System Exploration with Interactive Human Guidance
Bastien Morel, Clément Moulin-Frier, Pascal Barla
The diversity of patterns that emerge from complex systems motivates their use for scientific or artistic purposes. When exploring these systems, the challenges faced are the size…
Expedition & Expansion: Leveraging Semantic Representations for Goal-Directed Exploration in Continuous Cellular Automata
Sina Khajehabdollahi, Gautier Hamon, Marko Cvjetko +3
Discovering diverse visual patterns in continuous cellular automata (CA) is challenging due to the vastness and redundancy of high-dimensional behavioral spaces. Traditional explor…
Flow-Lenia: Emergent evolutionary dynamics in mass conservative continuous cellular automata
Erwan Plantec, Gautier Hamon, Mayalen Etcheverry +3
Central to the artificial life endeavour is the creation of artificial systems spontaneously generating properties found in the living world such as autopoiesis, self-replication,…
Exploring Flow-Lenia Universes with a Curiosity-driven AI Scientist: Discovering Diverse Ecosystem Dynamics
Thomas Michel, Marko Cvjetko, Gautier Hamon +2
We present a curiosity-driven AI scientist method for discovering system-level dynamics in Flow-Lenia, a continuous cellular automaton (CA) with mass conservation and parameter loc…
Emergent kin selection of altruistic feeding via non-episodic neuroevolution
Max Taylor-Davies, Gautier Hamon, Timothé Boulet +1
Kin selection theory has proven to be a popular and widely accepted account of how altruistic behaviour can evolve under natural selection. Hamilton's rule, first published in 1964…
Collective Innovation in Groups of Large Language Models
Eleni Nisioti, Sebastian Risi, Ida Momennejad +2
Human culture relies on collective innovation: our ability to continuously explore how existing elements in our environment can be combined to create new ones. Language is hypothes…
When LLMs Play the Telephone Game: Cultural Attractors as Conceptual Tools to Evaluate LLMs in Multi-turn Settings
Jérémy Perez, Grgur Kovač, Corentin Léger +5
As large language models (LLMs) start interacting with each other and generating an increasing amount of text online, it becomes crucial to better understand how information is tra…
Cultural evolution in populations of Large Language Models
Jérémy Perez, Corentin Léger, Marcela Ovando-Tellez +4
Research in cultural evolution aims at providing causal explanations for the change of culture over time. Over the past decades, this field has generated an important body of knowl…
Discovering Sensorimotor Agency in Cellular Automata using Diversity Search
Gautier Hamon, Mayalen Etcheverry, Bert Wang-Chak Chan +2
The research field of Artificial Life studies how life-like phenomena such as autopoiesis, agency, or self-regulation can self-organize in computer simulations. In cellular automat…
Evolving Reservoirs for Meta Reinforcement Learning
Corentin Léger, Gautier Hamon, Eleni Nisioti +2
Animals often demonstrate a remarkable ability to adapt to their environments during their lifetime. They do so partly due to the evolution of morphological and neural structures.…
Meta-Diversity Search in Complex Systems, A Recipe for Artificial Open-Endedness ?
Mayalen Etcheverry, Bert Wang-Chak Chan, Clément Moulin-Frier +1
Can we build an artificial system that would be able to generate endless surprises if ran "forever" in Minecraft? While there is not a single path toward solving that grand challen…
Emergence of Collective Open-Ended Exploration from Decentralized Meta-Reinforcement Learning
Richard Bornemann, Gautier Hamon, Eleni Nisioti +1
Recent works have proven that intricate cooperative behaviors can emerge in agents trained using meta reinforcement learning on open ended task distributions using self-play. While…
SBMLtoODEjax: Efficient Simulation and Optimization of Biological Network Models in JAX
Mayalen Etcheverry, Michael Levin, Clément Moulin-Frier +1
Advances in bioengineering and biomedicine demand a deep understanding of the dynamic behavior of biological systems, ranging from protein pathways to complex cellular processes. B…
Autotelic Reinforcement Learning in Multi-Agent Environments
Eleni Nisioti, Elías Masquil, Gautier Hamon +1
In the intrinsically motivated skills acquisition problem, the agent is set in an environment without any pre-defined goals and needs to acquire an open-ended repertoire of skills.…