Matthieu Geist

A Comprehensive Benchmark of Neural Networks for System Identification

2019 · HAL (Le Centre pour la Communication Scientifique Directe)

This paper compares a wide variety of neural network architectures applied in the context of black-box modeling for robotics and control. We compare six different architectural concepts and four activation functions, with over three hundred …

Adversarially Guided Actor-Critic

2021 · arXiv (Cornell University)

Despite definite success in deep reinforcement learning problems,\nactor-critic algorithms are still confronted with sample inefficiency in\ncomplex environments, particularly in tasks where efficient exploration is a\nbottleneck. These methods consider a policy (the actor) and a value …

Self-Imitation Advantage Learning

2021

Self-imitation learning is a Reinforcement Learning (RL) method that encourages actions whose returns were higher than expected, which helps in hard exploration and sparse reward problems. It was shown to improve the performance of on-policy …

A functional mirror ascent view of policy gradient methods with function approximation.

2021 · arXiv (Cornell University)

We use functional mirror ascent to propose a general framework (referred to as FMA-PG) for designing policy gradient methods. The functional perspective distinguishes between a policy's functional representation (what are its sufficient statistics) and its …