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Alberto-00 / Super-Mario-Bros-AI

The following project concerns the development of an intelligent agent for the famous game produced by Nintendo Super Mario Bros. More in detail: the goal of this project was to design, implement and train an agent with the Q-learning reinforcement learning algorithm.

deep-neural-networks reinforcement-learning qlearning reinforcement-learning-algorithms sarsa qlearning-algorithm reinforcement-learning-agent double-deep-q-network reinforcement-learning-environments sarsa-algorithm double-deep-q-learning double-deep-q-networks

Updated Dec 8, 2025
Python

Tahernezhad / Deep-Q-Learning-Stock-Trading

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DQN stock-trading agent with a custom Gymnasium environment and yfinance data.

finance reinforcement-learning time-series machine-learning-algorithms deep-reinforcement-learning pytorch dqn stocks gymnasium deep-q-learning dueling-dqn finance-data algoritmic-trading trading-strategy yfinance rl-trading quantative-finance double-deep-q-learning

Updated Jan 28, 2026
Python

kparnis3 / Final-Year-Project

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Undergraduate Dissertation (University of Malta) 2020-2023 - 'Autonomous Drone Control using Reinforcement Learning''

drone deep-reinforcement-learning obstacle-avoidance deep-q-learning obstacle-detection airsim trust-region-policy-optimization double-deep-q-learning

Updated Dec 4, 2023
Jupyter Notebook

flowun / gardnerChessAi

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Implementation of the Double Deep Q-Learning algorithm with a prioritized experience replay memory to train an agent to play the minichess variante Gardner Chess

chess reinforcement-learning ai tensorflow tutorials tensorflow-tutorials ddqn deep-q-learning double-dqn chess-ai prioritized-experience-replay q-value artificial-inteligence minichess double-deep-q-learning ai-projects

Updated Apr 2, 2024
Python

aniruddhapal211316 / mario_DDQN

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Play Super Mario Bros Game using Double Deep Q Network implemented in PyTorch.

reinforcement-learning pytorch mario-bros double-deep-q-network double-deep-q-learning

Updated Aug 23, 2023
Python

byrnesy924 / Yahtzee_Deep_Learning_Agent

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This project is a Double Deep Q learning Agent that learns to play the dice game Yahtzee

machine-learning reinforcement-learning deep-learning neural-network deep-reinforcement-learning q-learning artificial-intelligence artificial-neural-networks yahtzee yahtzee-game double-deep-q-network double-deep-q-learning double-deep-q-networks

Updated Mar 12, 2025
Python

iiShreya / Learning-Mario-Agent

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Learning Mario Agent with the Double Deep Q-Learning Algorithm in the Gym Super Mario Environment.

super-mario reinforcement-learning deep-learning q-learning pytorch rl densenet convolutional-neural-networks mario-game relu double-deep-q-learning

Updated Jun 30, 2022
Jupyter Notebook

Tahernezhad / Deep-Q-Learning-Workbench

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Clean, modular DQN in PyTorch with Double/Dueling options and MLP/CNN/LSTM backbones—plug-and-play for Gymnasium environments.

deep-reinforcement-learning openai-gym pytorch lstm reinforcement-learning-algorithms mlp gymnasium deep-q-learning pytho double-dqn dueling-dqn lunar-lander replay-buffer dq cnn1d double-deep-q-learning rl-benchmark

Updated Sep 23, 2025
Python

ethan-keller / DeepQLearning

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Model-free, off-policy reinforcement learning with DQN's on Gym's environments

reinforcement-learning deep-q-learning double-deep-q-learning

Updated Mar 16, 2023
Jupyter Notebook

Thanitkul / mario-rl

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This project uses Deep Q-Learning to train a Mario agent in a reinforcement learning environment. The agent is optimized using dynamic exploration rates, custom reward shaping, and Prioritized Experience Replay to improve learning efficiency.

reinforcement-learning gym double-deep-q-learning