Advisor:   Narayana Prasad Santhanam | nsanthan@hawaii.edu

Prerequisites:  No prerequisites for 296, Linear algebra (Math 307 or 345) for direct entry to 396, Linear algebra and probability (Math 307 or 345 and EE342) for direct entry to 496

Courses:  EE296, EE396, EE496

Focus:   W (Writing) O (Oral)

Description:  

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.

Goals: Automatic machine gameplay for strategy games

Key elements: Machine learning, Neural networks, LLMs, Large datasets, python

Advisors: Narayana Santhanam, Igor Molybog, and Liuwan Zhu

Sponsors and Partners: National Science Foundation

Majors, preparation and 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

Apply: If you are a new student interested in the project, please fill out the following form:

https://forms.gle/XnJpQM2HJ2nJB2vaA

and email Dr. Santhanam when you have completed the form.