[2023] Reinforcement learning basics
-
Updated
Oct 16, 2023 - Jupyter Notebook
[2023] Reinforcement learning basics
The program uses the DDPG algorithm and tf_agents library to train an agent in a custom environment called "TargetSeeker"
A deep learning model based on reinforcement learning to construct pathlet dictionaries.
Deep reinforcement learning agents for the Robotini racing simulator
Global Markets Options Pricing
Implementing Reinforcement Learning to develop an Agent that teaches itself to play the DemonAttack Atari Game. The Agent was developed using tensorflow, TF-Agents and OpenAI Gym Google Cloud Platform.
Reinforcement Learning (DQN, PPO, MCTS+DQN) for the classical game Bomberman.
training of a superhuman level Reinforcement Learning agent to play the Breakout Atari game.
Simple world models lead to good abstractions, Google Cerebra internship 2020/master thesis at EPFL LCN 2021 ⬛◼️▪️🔦
Reinforcement Learning applied to Object Avoidance
Tackling Atari 2600 game Pong with Reinforcement Learning by utilizing DQN and TF-Agents
Reinforcement learning (RL) Notes and Notebooks.
A TensorFlow based DQN agent who moves in a small grid world
Comparison of different Deep Reinforcement Learning (DRL) Frameworks. This repository includes "tf-agents", "RLlib" and will soon support "acme" as well.
Trade using DRL algorithms on tensorflow2 and tf-agents
TraderNet-CRv2 - Combining Deep Reinforcement Learning with Technical Analysis and Trend Monitoring on Cryptocurrency Markets
Reinforcement Learning for Practitioners.
Add a description, image, and links to the tf-agents topic page so that developers can more easily learn about it.
To associate your repository with the tf-agents topic, visit your repo's landing page and select "manage topics."