Q-urling (Quantum Curling)

[johnparkn]

Abstract

Define curling game in Markov Decision Process and find optimal strategy in the game using Qiskit Quantum Reinforcement learning.

Description

Curling is one of the favorite sports for spectators in the Winter Olympic game. Selecting a strategy is very important in playing curling (often called chess on ice). The entire curling game could be described into Markov Decision Process by expressing the strategy into aggressive and conservative ones[1]. Also, it is known that variational quantum circuits can perform reinforcement learning (policy-gradient) [2]. In this work, we will build a variational quantum circuit in Qiskit and train it to make this circuit decide the best strategy for playing curling.

Members

• @johnparkn
• @jaeunkim
• @chcy922
• @WestGround
• @anfry15rudals
• Qiskit Coach: @githubhandle

Reference

[1] Kiwook Beae, Dong Hyun Park, Dong Hyun Kim, and Hayong Shin, “Markov Decision Process for Curling Strategies,” Journal for Korean Institute of Industrial Engineers. Vol.42, No. 11, pp. 65-72, Feb 2016.
[2] Sofiene Jerbi, Casper Gyurik, Simon C. Marshall, Hans J. Briegel, and Vedran Dunjko, “Parameterized Quantum Policies for Reinforcement Learning”, Advances in Neural Information Processing System 34, 2021.

Deliverable

GitHub repo

QikskitQurling

[anfry15rudals]

참여합니다!

[WestGround]

참여합니다

[chcy922]

참여합니다 :)

[0sophy1]

팀 멤버 추가로 모집하시나요?

[jaeunkim]

참여합니다

[johnparkn]

팀 멤버 추가로 모집하시나요?

팀은 johnparkn, jaeunkim, chcy922, WestGround, anfry15rudals 5인으로 추가모집은 없을 예정입니다.

[0sophy1]

멘토 찾으셨나요~

[0sophy1]

이 프로젝트 발표자님! 저에게 이메일 주소 보내주세요! 슬랙에 Sophy! 최종 발표준비에 필요합니다

[0sophy1]

슬랙에 발표자들 공지 전달용 방을 하나 만들었으니 메시지 부탁드립니다!

[0sophy1]

발표자입니다 :) 이메일 주소는 입니다.
넵 접수했습니다. 스팸오니까 얼릉 이메일주소 지우세요 :)