Analiza algoritama poticanog učenja i primjena u implementaciji autonomnog igrača borbene računalne igre

undergraduate thesis

• Title (english): Analysis of Reinforcement Learning Algorithms With Application to Implementing an Autonomous Player of a Fighting Computer Game
• Author: Filip Antunović
• Mentor: Bogdan Okreša Đurić (mentor); MBZ: 367114
• Committee member: Markus Schatten (član povjerenstva); MBZ: 291806
• Granter: University of Zagreb; Faculty of Organization and Informatics; (Department of Theoretical and Applied Foundations of Information Sciences); Varaždin
• Defense date and country: 2022-09-26, Croatia
• Scientific / art field, discipline and subdiscipline: SOCIAL SCIENCES; Information and Communication Sciences; Organization and Informatics

Abstract

Ever since the first video game ’Pong’ was created by William Higinbotham back in 1958 people
have been fascinated with video games, how they work and most importantly how to make on of
their own. In the past decade we’ve seen more games than we can count, some of them being
League of Legends, Dota2, Call of Duty franchise, World of Warcraft, Fifa and many more. All
of these games have some sort of artificial intelligence spliced inside of them as NPC’s (non
playable characters) and with the rise in popularity and play rate of these games so has the
popularity in artificial intelligence. This peaked my interest and with that and information from
the Internet I’ve decided to make my own combat video game in which an autonomous player
will try to defeat an enemy using reinforcement learning.

• Keywords: umjetna inteligencija; unity; reinforcement learning; videoigre; poticano učenje
• Language: croatian
• URN:NBN: urn:nbn:hr:211:714803
• Study programme: Title: Information Systems; Study programme type: university; Study level: undergraduate; Academic / professional title: sveučilišni/a prvostupnik/prvostupnica (baccalaureus/baccalaurea) informatike (sveučilišni/a prvostupnik/prvostupnica (baccalaureus/baccalaurea) informatike)
• Type of resource: Text
• File origin: Born digital
• Access conditions: Access restricted to authenticated users
• Created on: 2022-10-03 04:26:24