Goals:
Automatic machine gameplay for strategy games
Key elements:
Machine learning, Neural networks, LLMs, Large datasets, Python
Research issues:
In this project, we will develop algorithms that automatically learn how to play board games. Here we will develop machine learning methods that observe gameplay, and automatically learn strategies from gameplay, pretty much how humans would. To this end, we will learn about machine learning, neural networks and Large Language Models (LLMs). We will be programming in python and you will also learn about toolsets developed for machine learning applications.
Meeting time:
TBD
Advisors:
Narayana Santhanam, Igor Molybog, and Liuwan Zhu
Partners and Sponsors:
National Science Foundation
Majors, preparation, interests:
geared towards SDS and Comp Eng students, but any Engineering/Math students with an interest in machine learning, neural networks, and artificial intelligence are welcome
Contact information:
Narayana Santhanam, nsanthan@hawaii.edu; Igor Molybog, molybog@hawaii.edu; Liuwan Zhu, liuwan@hawaii.edu