Bernardo Ávila Pires | DeepAI

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∙ 05/29/2023

DoMo-AC: Doubly Multi-step Off-policy Actor-Critic Algorithm

Multi-step learning applies lookahead over multiple time steps and has p...

0 Yunhao Tang, et al. ∙

∙ 03/02/2023

Understanding plasticity in neural networks

Plasticity, the ability of a neural network to quickly change its predic...

0 Clare Lyle, et al. ∙

∙ 02/28/2023

Hierarchical Reinforcement Learning in Complex 3D Environments

Hierarchical Reinforcement Learning (HRL) agents have the potential to d...

0 Bernardo Ávila Pires, et al. ∙

∙ 12/06/2022

Understanding Self-Predictive Learning for Reinforcement Learning

We study the learning dynamics of self-predictive learning for reinforce...

0 Yunhao Tang, et al. ∙

∙ 07/15/2022

The Nature of Temporal Difference Errors in Multi-step Distributional Reinforcement Learning

We study the multi-step off-policy learning approach to distributional R...

0 Yunhao Tang, et al. ∙

∙ 06/16/2022

BYOL-Explore: Exploration by Bootstrapped Prediction

We present BYOL-Explore, a conceptually simple yet general approach for ...

0 Zhaohan Daniel Guo, et al. ∙

∙ 02/03/2021

Neural Recursive Belief States in Multi-Agent Reinforcement Learning

In multi-agent reinforcement learning, the problem of learning to act is...

0 Pol Moreno, et al. ∙

∙ 01/06/2021

Geometric Entropic Exploration

Exploration is essential for solving complex Reinforcement Learning (RL)...

0 Zhaohan Daniel Guo, et al. ∙

∙ 06/13/2020

Bootstrap Your Own Latent: A New Approach to Self-Supervised Learning

We introduce Bootstrap Your Own Latent (BYOL), a new approach to self-su...

0 Jean-Bastien Grill, et al. ∙

∙ 04/30/2020

Bootstrap Latent-Predictive Representations for Multitask Reinforcement Learning

Learning a good representation is an essential component for deep reinfo...

0 Daniel Guo, et al. ∙

∙ 02/20/2019

World Discovery Models

As humans we are driven by a strong desire for seeking novelty in our wo...

0 Mohammad Gheshlaghi Azar, et al. ∙

∙ 09/20/2016

Multiclass Classification Calibration Functions

In this paper we refine the process of computing calibration functions f...

0 Bernardo Ávila Pires, et al. ∙

∙ 02/19/2016

Policy Error Bounds for Model-Based Reinforcement Learning with Factored Linear Models

In this paper we study a model-based approach to calculating approximate...

0 Bernardo Ávila Pires, et al. ∙

∙ 06/27/2012

Statistical Linear Estimation with Penalized Estimators: an Application to Reinforcement Learning

Motivated by value function estimation in reinforcement learning, we stu...

0 Bernardo Ávila Pires, et al. ∙

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