This work brings together the efforts of Narasimhan et al. and Adolphs et al. to tackle the task of building an AI agent that can play efficiently and win simplified text-based games.
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Nov 11, 2020 - Python
This work brings together the efforts of Narasimhan et al. and Adolphs et al. to tackle the task of building an AI agent that can play efficiently and win simplified text-based games.
A PyTorch implementation of a DQN agent to solve CartPole-V0 task from OpenAI Gym.
A Deep Reinforcement Learning Framework
Navigation Project - Udacity Deep Reinforcement Learning Nanodegree
PyTorch Implementations of Standard Deep RL Algorithms (including REINFORCE, A2C, PPO)
🌱CNN, GAN, RNN, DQN, Autoencoder, ResNet, Seq2Seq, Adversarial Attack IN PYTORCH
Deep Reinforcement Learning algorithms to play Connect4 using a combination of Supervised Learning and Reinforcement Learning
Implementation of Deep Q Learning algorithms in pytorch
Best solution on OpenAI Leaderboard(for Nov 2019)
Collaboration and Competition (using multi agent reinforcement learning). Train a pair of agents to play tennis.
deep reinforcement learning in pytorch
Implementation of upside down Reinforcement Learning
Modular Deep RL infrastructure in PyTorch
Deep Reinforcement Learning Nanodegree projects
Combining Improvements in Deep Reinforcement Learning
PPO implementation by using Pytorch C++ API
Reinforcement Learning modules for pytorch.
In this project, I have tried to use DeepRL for optimizing the selection of transactions done by the miner to increase the fee when they execute a block on the chain
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