Experiments testing variants of Value and Policy iterations.
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Updated
Jan 27, 2017 - Jupyter Notebook
Experiments testing variants of Value and Policy iterations.
Fundamentals of Reinforcement Learning
The homework for Cutting-Edge of Deep Learning, aka CEDL, from NTHU
Labs from Deep RL Bootcamp, 2017
A reinforcement learning agent navigating the OpenAI's FrozenLake environment
CSE 571 Artificial Intelligence
A Q Learning Reinforcement agent using a simple feed forward neural net.
A Markov Decision Process Algorithms Implementation
My reports for the reinforcement learning class given at the ENS
The homework for Cutting-Edge of Deep Learning, aka CEDL, from NTHU
Solutions for the labs in Deep RL Bootcamp.
Reinforcement Learning such as Q-Learn SARSA, lambda, policy iteration implemented in .NET
Implementations of basic concepts dealt under the Reinforcement Learning umbrella. This project is collection of assignments in CS747: Foundations of Intelligent and Learning Agents (Autumn 2017) at IIT Bombay
Reinforcement Learning projects from OpenAI Gym
CSCI561
Implementation of Policy Iteration and Value Iteration Agents for Taxi game of OpenAI gym
A digital policy consultation across a nation as a Rails App with two key elements: (a) a ‘collaborative policy-writing’ tool (b) a Facebook messenger bot. The consultation will be live for one month, after which the insight, feedback, and deliberation will be consolidated, integrated, and built into a revised citizen-driven national vision.
This includes sample reinfrocement learning algorithms .Currently working on an approach to use RL for more comlex navigation issues
Reinforcement-Learning-for-Decision-Making-in-self-driving-cars
Value Iteration and Policy Iteration to solve MDPs
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