229 citations · 274 across the 13 of their papers we have counts for
4 papers · 1 filter
A gray-box approach for curriculum learning
Francesco Foglino, Matteo Leonetti, Simone Sagratella +1
Curriculum learning is often employed in deep reinforcement learning to let the agent progress more quickly towards better behaviors. Numerical methods for curriculum learning in t…
Curriculum Learning for Cumulative Return Maximization
Francesco Foglino, Christiano Coletto Christakou, Ricardo Luna Gutierrez +1
Curriculum learning has been successfully used in reinforcement learning to accelerate the learning process, through knowledge transfer between tasks of increasing complexity. Crit…
Learning Physics-Based Manipulation in Clutter: Combining Image-Based Generalization and Look-Ahead Planning
Wissam Bejjani, Mehmet R. Dogar, Matteo Leonetti
Physics-based manipulation in clutter involves complex interaction between multiple objects. In this paper, we consider the problem of learning, from interaction in a physics simul…
An Optimization Framework for Task Sequencing in Curriculum Learning
Francesco Foglino, Christiano Coletto Christakou, Matteo Leonetti
Curriculum learning in reinforcement learning is used to shape exploration by presenting the agent with increasingly complex tasks. The idea of curriculum learning has been largely…