erenulu2020's repositories
Arnold
Arnold - DOOM Agent
attention-toad
Bickford Smith, Roads, Luo, Love (2021). Understanding top-down attention using task-oriented ablation design. arXiv:2106.11339.
baselines
OpenAI Baselines: high-quality implementations of reinforcement learning algorithms
Deep_reinforcement_learning_Course
Implementations from the free course Deep Reinforcement Learning with Tensorflow and PyTorch
DeepRL-Agents
A set of Deep Reinforcement Learning Agents implemented in Tensorflow.
DoorGym
Open source domain randomized door opening training environment
garage
A toolkit for reproducible reinforcement learning research.
keras-rl
Deep Reinforcement Learning for Keras.
KerasRL-OpenAI-Atari-SpaceInvadersv0
A notebook walking through how to use Keras RL to solve Atari environments.
lab
A customisable 3D platform for agent-based AI research
obstacle-tower-env
Obstacle Tower Environment
OpenAIPong-DQN
Solving Atari Pong Game w/ Duel Double DQN in Pytorch
PoPS
PoPS algorithm
pytorch-a2c-ppo-acktr-gail
PyTorch implementation of Advantage Actor Critic (A2C), Proximal Policy Optimization (PPO), Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation (ACKTR) and Generative Adversarial Imitation Learning (GAIL).
Reinforcement_Learning
Reinforcement learning tutorials
sam
Predicting Human Eye Fixations via an LSTM-based Saliency Attentive Model. IEEE Transactions on Image Processing (2018)
sample-factory
High throughput asynchronous reinforcement learning
scalable_agent
A TensorFlow implementation of Scalable Distributed Deep-RL with Importance Weighted Actor-Learner Architectures.
stella
A multi-platform Atari 2600 Emulator
TensorflowKeras-ReinforcementLearning
A tutorial walking through the use of Keras-RL for reinforcement learning with OpenAI gym.
unreal
Reinforcement learning with unsupervised auxiliary tasks
unrealwithattention
Attend Before you Act: Leveraging human visual attention for continual learning
ViZDoom
Doom-based AI Research Platform for Reinforcement Learning from Raw Visual Information. :godmode: