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08/25/2023
Integrating LLMs and Decision Transformers for Language Grounded Generative Quality-Diversity
Quality-Diversity is a branch of stochastic optimization that is often a...
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03/02/2023
Data-efficient, Explainable and Safe Payload Manipulation: An Illustration of the Advantages of Physical Priors in Model-Predictive Control
Machine Learning methods, such as those from the Reinforcement Learning ...
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10/21/2022
Random Actions vs Random Policies: Bootstrapping Model-Based Direct Policy Search
This paper studies the impact of the initial data gathering method on th...
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10/14/2022
E2R: a Hierarchical-Learning inspired Novelty-Search method to generate diverse repertoires of grasping trajectories
Robotics grasping refers to the task of making a robotic system pick an ...
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07/25/2022
Meta Neural Ordinary Differential Equations For Adaptive Asynchronous Control
Model-based Reinforcement Learning and Control have demonstrated great p...
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05/17/2022
Automatic Acquisition of a Repertoire of Diverse Grasping Trajectories through Behavior Shaping and Novelty Search
Grasping a particular object may require a dedicated grasping movement t...
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05/06/2022
Towards QD-suite: developing a set of benchmarks for Quality-Diversity algorithms
While the field of Quality-Diversity (QD) has grown into a distinct bran...
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05/06/2022
Geodesics, Non-linearities and the Archive of Novelty Search
The Novelty Search (NS) algorithm was proposed more than a decade ago. H...
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11/02/2021
Discovering and Exploiting Sparse Rewards in a Learned Behavior Space
Learning optimal policies in sparse rewards settings is difficult as the...
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09/28/2021
Exploratory State Representation Learning
Not having access to compact and meaningful representations is known to ...
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09/14/2021
Few-shot Quality-Diversity Optimisation
In the past few years, a considerable amount of research has been dedica...
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04/10/2021
Selection-Expansion: A Unifying Framework for Motion-Planning and Diversity Search Algorithms
Reinforcement learning agents need a reward signal to learn successful p...
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04/08/2021
BR-NS: an Archive-less Approach to Novelty Search
As open-ended learning based on divergent search algorithms such as Nove...
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02/05/2021
Sparse Reward Exploration via Novelty Search and Emitters
Reward-based optimization algorithms require both exploration, to find r...
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05/13/2020
Novelty Search makes Evolvability Inevitable
Evolvability is an important feature that impacts the ability of evoluti...
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05/13/2020
DREAM Architecture: a Developmental Approach to Open-Ended Learning in Robotics
Robots are still limited to controlled conditions, that the robot design...
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09/15/2019
State Representation Learning from Demonstration
In a context where several policies can be observed as black boxes on di...
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03/11/2019
Building an Affordances Map with Interactive Perception
Robots need to understand their environment to perform their task. If it...
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01/30/2019
Bootstrapping Robotic Ecological Perception from a Limited Set of Hypotheses Through Interactive Perception
To solve its task, a robot needs to have the ability to interpret its pe...
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01/03/2019
From exploration to control: learning object manipulation skills through novelty search and local adaptation
Programming a robot to deal with open-ended tasks remains a challenge, i...
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11/07/2018
Generative Adversarial Policy Networks for Behavioural Repertoire
Learning algorithms are enabling robots to solve increasingly challengin...
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07/24/2015