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In open-ended environments, autonomous learning agents must set their own goals and build their own curriculum through an intrinsically motivated exploration. They may consider a large diversity of goals, aiming to discover what is controllable in their environments, and what is not. Because some goals might prove easy and some impossible, agents must actively select which goal to practice at any moment, to maximize their overall mastery on the set of learnable goals. This paper proposes CURIOUS , an algorithm that leverages 1) a modular Universal Value Function Approximator with hindsight learning to achieve a diversity of goals of different kinds within a unique policy and 2) an automated curriculum learning mechanism that biases the attention of the agent towards goals maximizing the absolute learning progress. Agents focus sequentially on goals of increasing complexity, and focus back on goals that are being forgotten. Experiments conducted in a new modular-goal robotic environment show the resulting developmental self-organization of a learning curriculum, and demonstrate properties of robustness to distracting goals, forgetting and changes in body properties.
Author Information
Cédric Colas (Inria)
Pierre-Yves Oudeyer (Inria)
Dr. Pierre-Yves Oudeyer is Research Director (DR1) at Inria and head of the Inria and Ensta-ParisTech FLOWERS team (France). Before, he has been a permanent researcher in Sony Computer Science Laboratory for 8 years (1999-2007). After working on computational models of language evolution, he is now working on developmental and social robotics, focusing on sensorimotor development, language acquisition and life-long learning in robots. Strongly inspired by infant development, the mechanisms he studies include artificial curiosity, intrinsic motivation, the role of morphology in learning motor control, human-robot interfaces, joint attention and joint intentional understanding, and imitation learning. He has published a book, more than 80 papers in international journals and conferences, holds 8 patents, gave several invited keynote lectures in international conferences, and received several prizes for his work in developmental robotics and on the origins of language. In particular, he is laureate of the ERC Starting Grant EXPLORERS. He is editor of the IEEE CIS Newsletter on Autonomous Mental Development, and associate editor of IEEE Transactions on Autonomous Mental Development, Frontiers in Neurorobotics, and of the International Journal of Social Robotics. He is also working actively for the diffusion of science towards the general public, through the writing of popular science articles and participation to radio and TV programs as well as science exhibitions. Web:http://www.pyoudeyer.com and http://flowers.inria.fr
Olivier Sigaud (Sorbonne University)
Pierre Fournier (UPMC)
Mohamed Chetouani (UPMC)
Related Events (a corresponding poster, oral, or spotlight)
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2019 Oral: CURIOUS: Intrinsically Motivated Modular Multi-Goal Reinforcement Learning »
Tue Jun 11th 09:20 -- 09:25 PM Room Hall B
More from the Same Authors
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2021 Poster: TeachMyAgent: a Benchmark for Automatic Curriculum Learning in Deep RL »
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2021 Spotlight: TeachMyAgent: a Benchmark for Automatic Curriculum Learning in Deep RL »
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2019 Workshop: Exploration in Reinforcement Learning Workshop »
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2018 Poster: GEP-PG: Decoupling Exploration and Exploitation in Deep Reinforcement Learning Algorithms »
Cédric Colas · Olivier Sigaud · Pierre-Yves Oudeyer -
2018 Oral: GEP-PG: Decoupling Exploration and Exploitation in Deep Reinforcement Learning Algorithms »
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