Zuozhi Yang

PhD student at Drexel University

B.S. Gettysburg College 17'

Email: zy337[at]drexel[dot]edu

My research interests are artificial intelligence, machine learning, and their applications to games. I am currently focusing on integrating learning into search algorithms to improve their scalability.

Publications

Zuozhi Yang and Santiago Ontañón (2020) Integrating Search and Scripts for Real-Time Strategy Games: An Empirical Survey. In AAAI 2020 Workshop on Reinforcement Learning in Games. [PDF]
Zuozhi Yang and Santiago Ontanñón (2019). Guiding Monte Carlo Tree Search by Scripts in Real-Time Strategy Games. In proceedings of AIIDE 2019. [PDF]
Zuozhi Yang and Santiago Ontañón (2019) Extracting Policies from Replays to Improve MCTS in Real Time Strategy Games. In AAAI 2019 Knowledge Extraction from Games Workshop. [PDF]
Zuozhi Yang, Santiago Ontañón (2018) Learning Map-Independent Evaluation Functions for Real-Time Strategy Games. In Proceedings of IEEE-CIG 2018. [PDF]
Zuozhi Yang, Todd W. Neller (2017) A Monte Carlo Localization Assignment Using a Neato Vacuum with ROS. EAAI 2017 [PDF]
Todd W Neller, Colin M Messinger, Zuozhi Yang (2016) Learning and Using Hand Abstraction Values for Parameterized Poker Squares. EAAI 2016 [PDF]

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