Q Learning EV3 Robot Learning How to Walk
-
Updated
Aug 25, 2021 - Java
Q Learning EV3 Robot Learning How to Walk
Year-4 Module taken in NTU that focuses on reinforcement learning algorithms, single intelligent agent and multiagent systems.
Program created in java with swing interface.
Implémentation de l'algorithme the Q-learning avec JAVA : Version séquentielle et version multi-agents
Aplicação ANDROID. Implementação de MACHINE LEARNING.
Q-learning is a model-free reinforcement learning algorithm to learn the value of an action in a particular state. It does not require a model of the environment (hence "model-free"), and it can handle problems with stochastic transitions and rewards without requiring adaptations.
Reinforcement learning experiments
An efficient reinforcement learning algorithm for learning a strategy for game 2048
Maze solver using reinforcement learning methods (value iteration, policy iteration)
Experiments for a Q-Based Evolutionary Algorithm (QBEA)
Implementation of Reinforcement Learning
Add a description, image, and links to the reinforcement-learning-algorithms topic page so that developers can more easily learn about it.
To associate your repository with the reinforcement-learning-algorithms topic, visit your repo's landing page and select "manage topics."