229 citations · 274 across the 13 of their papers we have counts for
5 papers · 1 filter
Occlusion-Aware Search for Object Retrieval in Clutter
Wissam Bejjani, Wisdom C. Agboh, Mehmet R. Dogar +1
We address the manipulation task of retrieving a target object from a cluttered shelf. When the target object is hidden, the robot must search through the clutter for retrieving it…
Information-theoretic Task Selection for Meta-Reinforcement Learning
Ricardo Luna Gutierrez, Matteo Leonetti
In Meta-Reinforcement Learning (meta-RL) an agent is trained on a set of tasks to prepare for and learn faster in new, unseen, but related tasks. The training tasks are usually han…
Curriculum Learning with a Progression Function
Andrea Bassich, Francesco Foglino, Matteo Leonetti +1
Curriculum Learning for Reinforcement Learning is an increasingly popular technique that involves training an agent on a sequence of intermediate tasks, called a Curriculum, to inc…
Human-like Planning for Reaching in Cluttered Environments
Mohamed Hasan, Matthew Warburton, Wisdom C. Agboh +6
Humans, in comparison to robots, are remarkably adept at reaching for objects in cluttered environments. The best existing robot planners are based on random sampling of configurat…
Curriculum Learning for Reinforcement Learning Domains: A Framework and Survey
Sanmit Narvekar, Bei Peng, Matteo Leonetti +3
Reinforcement learning (RL) is a popular paradigm for addressing sequential decision tasks in which the agent has only limited environmental feedback. Despite many advances over th…