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2020-06-01 · A library of reinforcement learning components and agents.

reinforcement-learning acme deepmind research

2020-06-23 · We compare three approaches for automatically finding an appropriate augmentation combined with two novel regularization terms for the policy and value ...

data-augmentation reinforcement-learning kornia pytorch

2020-05-12 · A self-supervised reinforcement learning agent that tackles task-specific and the sample efficiency challenges.

self-supervised-learning reinforcement-learning plan2explore article

2020-06-18 · How can robots learn in changing, open-world environments? We introduce dynamic-parameter MDPs, to capture environments with persistent, unobserved ...

reinforcement-learning non-stationarity off-policy markov-decision-process

2020-06-30 · A survey of the integration of both fields, better known as model-based reinforcement learning.

reinforcement-learning markov-decision-process model-based-reinforcement-learning survey

2020-06-18 · In this work, we establish that self-attention can be viewed as a form of indirect encoding, which enables us to construct highly parameter-efficient ...

reinforcement-learning self-attention selective-attention neuroevolution

Reimplementation of Model-Agnostic Meta-Learning (MAML) applied on Reinforcement Learning problems in TensorFlow 2.

meta-learning reinforcement-learning tensorflow code

Blog article on Model-Based Offline Reinforcement Learning (MOReL) paper by Rahul Kidambi & Aravind Rajeswaran et al.

reinforcement-learning model-based offline-rl code

Blog Article on Behavior Regularized Offline Reinforcement Learning by Yifan Wu et al. (2019)

reinforcement-learning q-learning actor-critic tutorial

2020-06-12 · Blog article on Off-Policy Deep Reinforcement Learning without Exploration paper by Fujimoto et al. (ICML 2019)

reinforcement-learning q-learning batch-rl tutorial

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