Bellman Equation, Needleman-Warsh, Smith-Waterman Algorithms test and written in Ruby

Solving high dimensional HJB equation using tensor decomposition

CSCI-561 AI Assignments.

Implementation of Policy Iteration and Value Iteration Agents for Taxi game of OpenAI gym

Q-Learning from scratch in Python

Q-Value (Reinforcement Learning) on Grid World

Design and Implementation of Pac-Man Strategies with Embedded Markov Decision Process in a Dynamic, Non-Deterministic, Fully Observable Environment

Algorithms for Policy Evaluation, Estimation of Action Values, Policy Improvement, Policy Iteration, Truncated Policy Evaluation, Truncated Policy Iteration, Value Iteration . From Udacity's Deep Reinforcement Learning Nanodegree program.

Reinforcement Learning Light Riders Bot

Foundations Of Intelligent Learning Agents (FILA) Assignments

Repository for the Reinforcement Learning (CSE564) Fall'19 course at IIIT Delhi

Reinforcement learning

Reinforcement Learning을 이용한 Pac-Man 최적 경로 구하기

Using reinforcement learning to train a smartcab how to drive

calculate the optimum route in a warehouse using the Q-Learning algorithm (Bellman equation)

Implementing the Markov Decision process on a 2-D world.

Find the shortest route using A* algorithm and graphs (Route Planner application)

Personal implementation in C++ of http://www.cs.put.poznan.pl/mszubert/pub/szubert2014cig.pdf. Results could be reproduced. It's an algorithm that learns by itself to solve the 2048 game. It doesn't use deep learning (aka. neural networks). But it learns by itself using the Bellman equations.

Reinforcement Learning applied to Autonomous Networking to issue scheduling and decision to drones.