OpenAI LunarLander-v2 DeepRL-based solutions (DQN, DuelingDQN, D3QN)
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Updated
Aug 11, 2021 - Python
OpenAI LunarLander-v2 DeepRL-based solutions (DQN, DuelingDQN, D3QN)
A (very amateur) foreign exchange trading bot utilizing CNN + DQN.
Super Mario Bros training with Ray RLlib DQN algorithm
OpenAI MountainCar-v0 DeepRL-based solutions (DQN, DuelingDQN, D3QN)
Created an DQN AI Agent which chooses to sell, buy, or keep stocks from various companies.
An implementation of an Autonomous Vehicle Agent in CARLA simulator, using TF-Agents
Codes implementation of the paper "Deep reinforcement learning for minimizing tardiness in parallel machine scheduling with sequence dependent family setups"
Code for the paper "DQN-based ethical decision-making for self-driving cars in unavoidable crashes: An applied ethical knob."
In this repository there are the projects developed during the course of Advance Optimization-based Robot Control. The main topics are Task Space Inverse Dynamics (TSID), Differential Dynamic Programming (DDP) and Deep Q-Network (DQN).
a nearest frontier based DQN alg for robot exploration
A simple implementation of HFT (High-Frequency Trading) in Python on the concept of DQN for forex market
A DQN sample based on Keras or Tensorflow2.x using Maze env, which mainly take MorvanZhou's code for reference.
This repository focuses on anomaly detection with Reinforcement Learning. DQNs are used to approximate the value function for anomalies on timeseries. The repository is part of my Master Thesis in Computer Science
Implementation of reinforcement learning algorithms in a cyber security simulation. Autonomous and Adaptive Systems (University of Bologna, Italy) course project.
Apply DQN model in reinforcement learning to build an AI model with the goal of mastering tic tac toe game.
simulation platform for algorithmic pricing
Solving MountainCar-v0 environment in Keras with Deep Q Learning an Deep Reinforcement Learning algorithm
Atari OpenAI Pong-v4 DeepRL-based solutions (DQN, DuelingDQN, D3QN)
Project code for my seminar paper
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