Stroj za igru šah zasnovan na podržanom učenju

undergraduate thesis

• Title (english): Chess Game Engine Based on Reinforcement Learning
• Author: Mladen Džida
• Mentor: Marin Šilić (mentor)
• Committee member: Marin Šilić (predsjednik povjerenstva)
• Committee member: Lucija Šikić (član povjerenstva)
• Committee member: Davor Vukadin (član povjerenstva)
• Granter: University of Zagreb; Faculty of Electrical Engineering and Computing; Zagreb
• Defense date and country: 2021-07-07, Croatia
• Scientific / art field, discipline and subdiscipline: TECHNICAL SCIENCES; Computing

Abstract

U 2017. godini je DeepMind izdao rad u kojem je opisao glavnu ideju kako ostvariti
šahovski stroj temeljen na dubokom podržanom učenju. Ovaj rad se bavi implementiranjem
opisanog algoritma na jedinstven način. Algoritam se temelji na dubokom
podržanom učenju, odnosno na neuronskim mrežama i algoritmima podržanog
učenja. U izradi se koriste rezidualne neuronske mreže koje omogućavaju izradu vrlo
dubokih mreža, tj. mreža s puno slojeva. Korišteni algoritam podržanog učenja je
obilazak stabla tehnikom Monte Carlo. Implementacijom neuronskih mreža i Monte
Carlo algoritma se gradi model šahovskog stroja te se on uči koji su potezi dobri na
temelju nagrada i kazni koje dobije u partijama koje igra sam sa sobom. Izgrađeni stroj
ima još dosta mjesta za nadogradnje.

Abstract (english)

In 2017, DeepMind published a paper describing the main idea of how to realize a
chess machine based on deep reinforcement learning. This paper deals with the implementation
of the described algorithm in a unique way. The algorithm is based on deep
reinforcement learning, i.e. neural networks and reinforcement learning algorithms.
Residual neural networks are used in designing the model, which enable very deep
networks, i.e. networks with many layers. The supported learning algorithm used is
a tree tour using the Monte Carlo technique. By implementing neural networks and
the Monte Carlo algorithm, a model of a chess machine is built and one learns which
moves are good based on the reward and punishment received in the games they play
with. The built machine still has plenty of room to upgrade.

• Keywords: duboko podržano učenje; rezidualna neuronske mreža; obilazak stabla tehnikom Monte Carlo
• Keywords (english): deep reinforcement learning; residual neural network; Monte Carlo tree search
• Language: croatian
• URN:NBN: urn:nbn:hr:168:955093
• Study programme: Title: Computing; Study programme type: university; Study level: undergraduate; Academic / professional title: sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka računarstva (sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka računarstva)
• Type of resource: Text
• File origin: Born digital
• Access conditions: Closed access
• Created on: 2023-01-14 20:21:19