Javascript must be enabled for the correct page display

Learning hearts by using reinforcement learning, neural networks and rollout methods

Miedema, daniel (2018) Learning hearts by using reinforcement learning, neural networks and rollout methods. Bachelor's Thesis, Artificial Intelligence.

[img]
Preview
Text
AI_BA_2018_DanielMiedema.pdf

Download (194kB) | Preview
[img] Text
toestemming.pdf
Restricted to Registered users only

Download (92kB)

Abstract

In this study reinforcement learning is used to play the card game hearts, an imperfect state information game. An agent uses Monte Carlo learning, Monte Carlo rollouts, and Neural Networks to play the game. This paper explains the inner workings of this agent and will specifically look at the extension of the rollout method and its parameters, for the possibilities to increase the performance. A neural network based agent will be compared with a rollout based agent for testing, from which we conclude that the rollout method, as implemented in this study, cannot outperform the neural network when enough training time is given.

Item Type: Thesis (Bachelor's Thesis)
Supervisor:
Supervisor nameSupervisor E mail
Wiering, M.A.M.A.Wiering@rug.nl
Degree programme: Artificial Intelligence
Thesis type: Bachelor's Thesis
Language: English
Date Deposited: 30 Oct 2018
Last Modified: 02 Nov 2018 11:34
URI: http://fse.studenttheses.ub.rug.nl/id/eprint/18766

Actions (login required)

View Item View Item