1 code implementation • 13 Mar 2024 • Jérémy Perez, Corentin Léger, Marcela Ovando-Tellez, Chris Foulon, Joan Dussauld, Pierre-Yves Oudeyer, Clément Moulin-Frier
We here present a framework for simulating cultural evolution in populations of LLMs, allowing the manipulation of variables known to be important in cultural evolution, such as network structure, personality, and the way social information is aggregated and transformed.
1 code implementation • 14 Feb 2024 • Gautier Hamon, Mayalen Etcheverry, Bert Wang-Chak Chan, Clément Moulin-Frier, Pierre-Yves Oudeyer
The research field of Artificial Life studies how life-like phenomena such as autopoiesis, agency, or self-regulation can self-organize in computer simulations.
2 code implementations • 9 Dec 2023 • Corentin Léger, Gautier Hamon, Eleni Nisioti, Xavier Hinaut, Clément Moulin-Frier
At the developmental scale, we employ these evolved reservoirs to facilitate the learning of a behavioral policy through Reinforcement Learning (RL).
no code implementations • 1 Dec 2023 • Mayalen Etcheverry, Bert Wang-Chak Chan, Clément Moulin-Frier, Pierre-Yves Oudeyer
Holmes incrementally learns a hierarchy of modular representations to characterize divergent sources of diversity and uses a goal-based intrinsically-motivated exploration as the diversity search strategy.
no code implementations • 1 Nov 2023 • Richard Bornemann, Gautier Hamon, Eleni Nisioti, Clément Moulin-Frier
We further find that the agents learned collective exploration strategies extend to an open ended task setting, allowing them to solve task trees of twice the depth compared to the ones seen during training.
1 code implementation • 17 Jul 2023 • Mayalen Etcheverry, Michael Levin, Clément Moulin-Frier, Pierre-Yves Oudeyer
Advances in bioengineering and biomedicine demand a deep understanding of the dynamic behavior of biological systems, ranging from protein pathways to complex cellular processes.
1 code implementation • 16 May 2023 • Eleni Nisioti, Clément Moulin-Frier
In this work, we study NC in simulation environments that consist of multiple, diverse niches and populations that evolve their plasticity, evolvability and niche-constructing behaviors.
1 code implementation • 18 Feb 2023 • Gautier Hamon, Eleni Nisioti, Clément Moulin-Frier
Neuroevolution (NE) has recently proven a competitive alternative to learning by gradient descent in reinforcement learning tasks.
1 code implementation • 14 Dec 2022 • Erwan Plantec, Gautier Hamon, Mayalen Etcheverry, Pierre-Yves Oudeyer, Clément Moulin-Frier, Bert Wang-Chak Chan
Finally, we show that Flow Lenia enables the integration of the parameters of the CA update rules within the CA dynamics, making them dynamic and localized, allowing for multi-species simulations, with locally coherent update rules that define properties of the emerging creatures, and that can be mixed with neighbouring rules.
no code implementations • 5 Dec 2022 • Martí Sánchez-Fibla, Clément Moulin-Frier, Ricard Solé
This includes major innovations that allowed to reduce and control the impact of extreme events.
no code implementations • 3 Oct 2022 • Tristan Karch, Yoann Lemesle, Romain Laroche, Clément Moulin-Frier, Pierre-Yves Oudeyer
In this paper, we investigate whether artificial agents can develop a shared language in an ecological setting where communication relies on a sensory-motor channel.
no code implementations • 10 Jun 2022 • Eleni Nisioti, Mateo Mahaut, Pierre-Yves Oudeyer, Ida Momennejad, Clément Moulin-Frier
Comparing the level of innovation achieved by different social network structures across different tasks shows that, first, consistent with human findings, experience sharing within a dynamic structure achieves the highest level of innovation in tasks with a deceptive nature and large search spaces.
Cultural Vocal Bursts Intensity Prediction Reinforcement Learning (RL)
no code implementations • 2 Jun 2022 • Cédric Colas, Tristan Karch, Clément Moulin-Frier, Pierre-Yves Oudeyer
Building autonomous agents able to grow open-ended repertoires of skills across their lives is a fundamental goal of artificial intelligence (AI).
1 code implementation • 17 Feb 2022 • Eleni Nisioti, Clément Moulin-Frier
In this work, we study the interplay between environmental dynamics and adaptation in a minimal model of the evolution of plasticity and evolvability.
1 code implementation • ICLR 2022 • Paul Barde, Tristan Karch, Derek Nowrouzezahrai, Clément Moulin-Frier, Christopher Pal, Pierre-Yves Oudeyer
ABIG results in a low-level, high-frequency, guiding communication protocol that not only enables an architect-builder pair to solve the task at hand, but that can also generalize to unseen tasks.
no code implementations • 20 Sep 2021 • Julius Taylor, Eleni Nisioti, Clément Moulin-Frier
In this work, we propose that aligning internal subjective representations, which naturally arise in a multi-agent setup where agents receive partial observations of the same underlying environmental state, can lead to more data-efficient representations.
1 code implementation • NeurIPS 2021 • Tristan Karch, Laetitia Teodorescu, Katja Hofmann, Clément Moulin-Frier, Pierre-Yves Oudeyer
While there is an extended literature studying how machines can learn grounded language, the topic of how to learn spatio-temporal linguistic concepts is still largely uncharted.
no code implementations • 15 Dec 2020 • Eleni Nisioti, Clément Moulin-Frier
Recent advances in Artificial Intelligence (AI) have revived the quest for agents able to acquire an open-ended repertoire of skills.
2 code implementations • NeurIPS 2020 • Cédric Colas, Tristan Karch, Nicolas Lair, Jean-Michel Dussoux, Clément Moulin-Frier, Peter Dominey, Pierre-Yves Oudeyer
We argue that the ability to imagine out-of-distribution goals is key to enable creative discoveries and open-ended learning.
2 code implementations • 9 Oct 2020 • Cédric Colas, Boris Hejblum, Sébastien Rouillon, Rodolphe Thiébaut, Pierre-Yves Oudeyer, Clément Moulin-Frier, Mélanie Prague
Epidemiologists model the dynamics of epidemics in order to propose control strategies based on pharmaceutical and non-pharmaceutical interventions (contact limitation, lock down, vaccination, etc).
no code implementations • ICML Workshop LaReL 2020 • Tristan Karch, Nicolas Lair, Cédric Colas, Jean-Michel Dussoux, Clément Moulin-Frier, Peter Ford Dominey, Pierre-Yves Oudeyer
We introduce the Playground environment and study how this form of goal imagination improves generalization and exploration over agents lacking this capacity.
no code implementations • 20 Mar 2020 • Tristan Karch, Cédric Colas, Laetitia Teodorescu, Clément Moulin-Frier, Pierre-Yves Oudeyer
This paper investigates the idea of encoding object-centered representations in the design of the reward function and policy architectures of a language-guided reinforcement learning agent.
2 code implementations • 21 Feb 2020 • Cédric Colas, Tristan Karch, Nicolas Lair, Jean-Michel Dussoux, Clément Moulin-Frier, Peter Ford Dominey, Pierre-Yves Oudeyer
We argue that the ability to imagine out-of-distribution goals is key to enable creative discoveries and open-ended learning.
no code implementations • 20 Feb 2020 • Clément Moulin-Frier, Pierre-Yves Oudeyer
Computational models of emergent communication in agent populations are currently gaining interest in the machine learning community due to recent advances in Multi-Agent Reinforcement Learning (MARL).
BIG-bench Machine Learning Multi-agent Reinforcement Learning +3
1 code implementation • 12 Jun 2017 • Clément Moulin-Frier, Tobias Fischer, Maxime Petit, Grégoire Pointeau, Jordi-Ysard Puigbo, Ugo Pattacini, Sock Ching Low, Daniel Camilleri, Phuong Nguyen, Matej Hoffmann, Hyung Jin Chang, Martina Zambelli, Anne-Laure Mealier, Andreas Damianou, Giorgio Metta, Tony J. Prescott, Yiannis Demiris, Peter Ford Dominey, Paul F. M. J. Verschure
This paper introduces a cognitive architecture for a humanoid robot to engage in a proactive, mixed-initiative exploration and manipulation of its environment, where the initiative can originate from both the human and the robot.
no code implementations • 5 Apr 2017 • Clément Moulin-Frier, Jordi-Ysard Puigbò, Xerxes D. Arsiwalla, Martì Sanchez-Fibla, Paul F. M. J. Verschure
In this paper, we argue that the future of Artificial Intelligence research resides in two keywords: integration and embodiment.
no code implementations • 31 Dec 2013 • Steve N'Guyen, Clément Moulin-Frier, Jacques Droulez
Schematically, two main approaches have been followed: either the agent learns which option is the correct one to choose in a given situation by trial and error, or the agent already has some knowledge on the possible consequences of his decisions; this knowledge being generally expressed as a conditional probability distribution.
no code implementations • 20 Sep 2013 • Clément Moulin-Frier, M. A. Arbib
The core tenet of the model is that the listener uses hypotheses about the word the speaker is currently uttering to update probabilities linking the sound produced by the speaker to phonemes in the native language repertoire of the listener.