The purpose of this thesis is to develop an agent that learns to play an interpretation ofthe popular game Ticket To Ride. This project is done in collaboration with Piktiv AB.This thesis presents how an agent based on the Double Deep Q-network algorithm learnsto play a version of Ticket To Ride using self-play. This is the documentation of how thegame and the agent was developed, as well as how the agent was evaluated.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:oru-99988 |
| Date | January 2022 |
| Creators | Strömberg, Linus, Lind, Viktor |
| Publisher | Örebro universitet, Institutionen för naturvetenskap och teknik |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
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