[파이썬과 케라스로 배우는 강화학습] 예제
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Updated
Oct 28, 2020 - Python
[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.
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
MatrixWorld: A pursuit-evasion platform for safe multi-agent coordination and autocurricula
Agent-based activity generation of runners for city infrastructure planning.
A TensorFlow based DQN agent who moves in a small grid world
Modeling of urban form based on the 'Beady Ring' model (Hillier & Hanson, 1984) using deep reinforcement learning.
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.
A variety of novelty search for agents evolving in grid worlds.
Q learning with neural network based function approximators.
Multi-agent pursuit in matrix world (pursuitMW)
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.
Reinforcement Learning
Basic example of A* search
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