An efficient reinforcement learning algorithm for learning a strategy for game 2048
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Updated
Mar 4, 2017 - Java
An efficient reinforcement learning algorithm for learning a strategy for game 2048
Developed By "Perfect Cube"
Program created in java with swing interface.
Q Learning EV3 Robot Learning How to Walk
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.
Using Burlap RL library templates for a more modern experience with burlap
Year-4 Module taken in NTU that focuses on reinforcement learning algorithms, single intelligent agent and multiagent systems.
Reinforcement learning experiments
Experiments for a Q-Based Evolutionary Algorithm (QBEA)
Implémentation de l'algorithme the Q-learning avec JAVA : Version séquentielle et version multi-agents
Aplicação ANDROID. Implementação de MACHINE LEARNING.
Maze solver using reinforcement learning methods (value iteration, policy iteration)
Implementation of Reinforcement Learning
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