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We perform functional grounding of LLMs' knowledge in BabyAI-Text
A minimal PyTorch re-implementation of the OpenAI GPT (Generative Pretrained Transformer) training
DQN Zoo is a collection of reference implementations of reinforcement learning agents developed at DeepMind based on the Deep Q-Network (DQN) agent.
OPE Tools based on Empirical Study of Off Policy Policy Estimation paper.
Google Research
An index of algorithms for offline reinforcement learning (offline-rl)
PIC: Permutation Invariant Critic for Multi-Agent Deep Reinforcement Learning
A curated list of awesome model based RL resources (continually updated)
Question Answering with Interactive Text (QAit), code for EMNLP 2019 paper "Interactive Language Learning by Question Answering"
A booklet on machine learning systems design with exercises. NOT the repo for the book "Designing Machine Learning Systems"
Simple and easily configurable grid world environments for reinforcement learning
BabyAI platform. A testbed for training agents to understand and execute language commands.
cordial-sync is a software package than can be used to reproduce the results from the paper "A Cordial Sync: Going Beyond Marginal Policies for Multi-Agent Embodied Tasks”
RAD: Reinforcement Learning with Augmented Data
Code for paper "Not All Unlabeled Data are Equal: Learning to Weight Data in Semi-supervised Learning", Ren et al., NeurIPS'20
Official Implementation of Learning Diverse and Discriminative Representations via the Principle of Maximal Coding Rate Reduction (2020)
Tensorflow 2 source code for the PI-SAC agent from "Predictive Information Accelerates Learning in RL" (NeurIPS 2020)
A learning environment for man-made Interactive Fiction games.
The release codes of LA-MCTS with its application to Neural Architecture Search.
Estimators for the entropy and other information theoretic quantities of continuous distributions
SEED RL: Scalable and Efficient Deep-RL with Accelerated Central Inference. Implements IMPALA and R2D2 algorithms in TF2 with SEED's architecture.
PyTorch implementations of deep reinforcement learning algorithms and environments
Sacred is a tool to help you configure, organize, log and reproduce experiments developed at IDSIA.