[파이썬과 케라스로 배우는 강화학습] 예제

A Test-Implementation of the IMPALA algorithm (by deepmind 2018)

Gridworld environment creator for testing RL algorithms

See a program learn the best actions in a grid-world to get to the target cell, and even run through the grid in real-time! This is a Q-Learning implementation for 2-D grid world using both epsilon-greedy and Boltzmann exploration policies.

Agent-based activity generation of runners for city infrastructure planning.

MatrixWorld: A pursuit-evasion platform for safe multi-agent coordination and autocurricula

Python implementation for Reinforcement Learning algorithms -- Bandit algorithms, MDP, Dynamic Programming (value/policy iteration), Model-free Control (off-policy Monte Carlo, Q-learning)

A grid world simulation environment

Modeling of urban form based on the 'Beady Ring' model (Hillier & Hanson, 1984) using deep reinforcement learning.

A TensorFlow based DQN agent who moves in a small grid world

Reinforcement learning agent which finds a path to the goal in a grid world. This exercise was done as a coursework for course C424 at Imperial College London.

Multi-agent pursuit in matrix world (pursuitMW)

Q learning with neural network based function approximators.

A variety of novelty search for agents evolving in grid worlds.

Reinforcement Learning code to solve Grid World game

Deep Reinforcement Learning implementation of Policy Gradient on a simple Grid-World problem using PyTorch.

My Grid World Application. Presented in class on April 7th, 2023.

Implementation of some Reinforcement Learning methods for grid world in Python

Reinforcement Learning

Basic example of A* search