Repository for the Reinforcement Learning (CSE564) Fall'19 course at IIIT Delhi
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Updated
Dec 6, 2019 - Jupyter Notebook
Repository for the Reinforcement Learning (CSE564) Fall'19 course at IIIT Delhi
Provides methods to efficiently set up and solve dynamic programming problems of one choice variable using Value Function Iteration and the Endogenous Grid Method.
Implementing the Markov Decision process on a 2-D world.
Foundations Of Intelligent Learning Agents (FILA) Assignments
Reinforcement Learning을 이용한 Pac-Man 최적 경로 구하기
Simulation of Routing Algorithms used in communication networks in python
A Markov Decision Process (MDP) based implementation of a Pacman agent, to survive and battle through a handicapped stochastic environment.
Jupyter notebooks implementing Reinforcement Learning algorithms in Numpy and Tensorflow
Game Tic-Tac-Toe with Q_learning algorithm
Optimal solution computation 💹 for macroeconomic models 🤑 with dynamic programming in python 🐍
Projects and Models built in Python leveraging PyTorch, implementing Reinforcement Learning algorithms for reward-based tasks.
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.
Repository for the code of the "Dynamic Programming and Optimal Control" (DPOC) lecture at the "Institute for Dynamic Systems and Control" at ETH Zurich.
Bellman Equation, Needleman-Warsh, Smith-Waterman Algorithms test and written in Ruby
Reinforcement Learning Light Riders Bot
Mountain Car is a Gym environment. I used this environment to train my model using Q-Learning which is a reinforcement learning technic.
CZ4046: Intelligent Agents - Assignment 1
Asteroids evasion using OpenAI's gym Reinforcement Learning (RL) package - M.Sc. Thesis in Computer Science, Ben Gurion University Ben Gurion University of the Negev, Israe
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