Zobrazeno 1 - 10
of 14
pro vyhledávání: '"Teodorescu, Laetitia"'
Autor:
Nisioti, Eleni, Glanois, Claire, Najarro, Elias, Dai, Andrew, Meyerson, Elliot, Pedersen, Joachim Winther, Teodorescu, Laetitia, Hayes, Conor F., Sudhakaran, Shyam, Risi, Sebastian
Large Language Models (LLMs) have taken the field of AI by storm, but their adoption in the field of Artificial Life (ALife) has been, so far, relatively reserved. In this work we investigate the potential synergies between LLMs and ALife, drawing on
Externí odkaz:
http://arxiv.org/abs/2407.09502
The ability to invent novel and interesting problems is a remarkable feature of human intelligence that drives innovation, art, and science. We propose a method that aims to automate this process by harnessing the power of state-of-the-art generative
Externí odkaz:
http://arxiv.org/abs/2310.10692
Autor:
Colas, Cédric, Teodorescu, Laetitia, Oudeyer, Pierre-Yves, Yuan, Xingdi, Côté, Marc-Alexandre
Humans learn to master open-ended repertoires of skills by imagining and practicing their own goals. This autotelic learning process, literally the pursuit of self-generated (auto) goals (telos), becomes more and more open-ended as the goals become m
Externí odkaz:
http://arxiv.org/abs/2305.12487
Building open-ended agents that can autonomously discover a diversity of behaviours is one of the long-standing goals of artificial intelligence. This challenge can be studied in the framework of autotelic RL agents, i.e. agents that learn by selecti
Externí odkaz:
http://arxiv.org/abs/2302.05244
In this extended abstract we discuss the opportunities and challenges of studying intrinsically-motivated agents for exploration in textual environments. We argue that there is important synergy between text environments and autonomous agents. We ide
Externí odkaz:
http://arxiv.org/abs/2207.04118
Autor:
Karch, Tristan, Teodorescu, Laetitia, Hofmann, Katja, Moulin-Frier, Clément, Oudeyer, Pierre-Yves
Publikováno v:
Neurips 2021
Language is an interface to the outside world. In order for embodied agents to use it, language must be grounded in other, sensorimotor modalities. While there is an extended literature studying how machines can learn grounded language, the topic of
Externí odkaz:
http://arxiv.org/abs/2106.08858
Recognizing precise geometrical configurations of groups of objects is a key capability of human spatial cognition, yet little studied in the deep learning literature so far. In particular, a fundamental problem is how a machine can learn and compare
Externí odkaz:
http://arxiv.org/abs/2004.04546
Autor:
Karch, Tristan, Colas, Cédric, Teodorescu, Laetitia, Moulin-Frier, Clément, Oudeyer, Pierre-Yves
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. This is done using a combination of object-wise permutation
Externí odkaz:
http://arxiv.org/abs/2003.09443
Autor:
Karch, Tristan, Colas, Cédric, Teodorescu, Laetitia, Moulin-Frier, Clément, Oudeyer, Pierre-Yves
Publikováno v:
Beyond Tabula Rasa in Reinforcement Learning: agents that remember adapt and generalize, Workshop at ICLR
Beyond Tabula Rasa in Reinforcement Learning: agents that remember adapt and generalize, Workshop at ICLR, Apr 2021, Addis Ababa, Ethiopia
Beyond Tabula Rasa in Reinforcement Learning: agents that remember adapt and generalize, Workshop at ICLR, Apr 2021, Addis Ababa, Ethiopia
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. This is done using a combination of object-wise permutation
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0b2fe8b7313cb043c504615f4aa392dc
https://hal.inria.fr/hal-03120669
https://hal.inria.fr/hal-03120669
Publikováno v:
Frontiers in Artificial Intelligence, Vol 4 (2022)
An embodied, autonomous agent able to set its own goals has to possess geometrical reasoning abilities for judging whether its goals have been achieved, namely it should be able to identify and discriminate classes of configurations of objects, irres
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::938a1e87c588ff4021eec67c877a5689
https://hal.inria.fr/hal-03117819/file/spatialsim_paper.pdf
https://hal.inria.fr/hal-03117819/file/spatialsim_paper.pdf