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https://openreview.net/forum?id=vS0R9cDHFN&referrer=%5Bthe%20profile%20of%20Sergey%20Levine%5D(%2Fprofile%3Fid%3D~Sergey_Levine1) Value-Based Deep RL Scales Predictably | OpenReview Scaling data and compute is critical to the success of modern ML. However, scaling demands predictability: we want methods to not only perform well with more... value based deep rl scales predictably openreview https://openreview.net/forum?id=KzR07JhgtW A Theoretical Explanation of Deep RL Performance in Stochastic Environments | OpenReview Reinforcement learning (RL) theory has largely focused on proving minimax sample complexity bounds. These require _strategic_ exploration algorithms that use... deep rl theoretical explanation https://openreview.net/forum?id=AnFUgNC3Yc Resetting the Optimizer in Deep RL: An Empirical Study | OpenReview We focus on the task of approximating the optimal value function in deep reinforcement learning. This iterative process is comprised of solving a sequence of... the optimizer in deep empirical study resetting rl https://openreview.net/forum?id=vS0R9cDHFN Value-Based Deep RL Scales Predictably | OpenReview Scaling data and compute is critical to the success of modern ML. However, scaling demands predictability: we want methods to not only perform well with more... value based deep rl scales predictably openreview https://jmlr.org/papers/v22/21-0657.html VariBAD: Variational Bayes-Adaptive Deep RL via Meta-Learning variational bayes deep rl adaptive via meta https://deepai.org/publication/impala-scalable-distributed-deep-rl-with-importance-weighted-actor-learner-architectures IMPALA: Scalable Distributed Deep-RL with Importance Weighted Actor-Learner Architectures | DeepAI Feb 5, 2018 - 02/05/18 - In this work we aim to solve a large collection of tasks using a single reinforcement learning agent with a single set of paramete... deep rl https://openreview.net/forum?id=-Txy_1wHJ4f Safe Deep RL in 3D Environments using Human Feedback | OpenReview Agents should avoid unsafe behaviour during both training and deployment. This typically requires a simulator and a procedural specification of unsafe... deep rl in 3d safe environments using https://openreview.net/forum?id=9GzyCtlngK Compute-Optimal Scaling for Value-Based Deep RL | OpenReview As models grow larger and training them becomes expensive, it becomes increasingly important to scale training recipes not just to larger models and more data,... value based deep rl compute optimal scaling https://openreview.net/forum?id=LYYhPFpcv95 Noisy Symbolic Abstractions for Deep RL: A case study with Reward Machines | OpenReview We learn RL policies for reward machine tasks under noisy symbolic abstractions a case study https://openreview.net/forum?id=qaHrpITIvB Counteractive RL: Rethinking Core Principles for Efficient and Scalable Deep Reinforcement Learning... Following the pivotal success of learning strategies to win at tasks, solely by interacting with an environment without any supervision, agents have gained the... core principles