[Eecs_msee] New EE/CS 4900/5900/6900 Courses

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Spring 2024 CS 4900/5900 – Game AI (Artificial Intelligence in Games)

Instructor:               Dr. Chang Liu ( liuc at ohio.edu 
<mailto: liuc at ohio.edu 
>)
Credits:                3
Class Meetings:          Tu/Th 5:00pm-6:20pm @ ARC 314  
Office Hours:           Thursdays from 9 to 11am @ Stocker 321c

Course Description:

A course that focuses on computational intelligence for computer video games. Topics include classical Markov decision processes, Monte Carlo tree search, tabular reinforcement learning methods, and reinforcement learning with deep neural networks. All students will participate in simulated game AI competitions using the MicroRTS platform ( https://github.com/Farama-Foundation/MicroRTS<https://nam11.safelinks.protection.outlook.com/?url=https%3A%2F%2Fgithub.com%2FFarama-Foundation%2FMicroRTS&data=05%7C01%7Ceecs_msee%40listserv.ohio.edu%7C26ac87641e4d4df3fc8f08dbe067d248%7Cf3308007477c4a70888934611817c55a%7C0%7C0%7C638350508755704969%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=GRvSmxEOoDQghQj6aqTbL0s2n5pkKwfMz%2FRx2Xw1F1g%3D&reserved=0 
>) or StarCraft II. Students will be encouraged to compete in the IEEE Conference on Games (CoG) competition of game AI ( https://2024.ieee-cog.org/competitions/<https://nam11.safelinks.protection.outlook.com/?url=https%3A%2F%2F2024.ieee-cog.org%2Fcompetitions%2F&data=05%7C01%7Ceecs_msee%40listserv.ohio.edu%7C26ac87641e4d4df3fc8f08dbe067d248%7Cf3308007477c4a70888934611817c55a%7C0%7C0%7C638350508755704969%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=gGvT3f16flyW9eQB7Nx3KpfpGVGR37paERmd8NhEr2I%3D&reserved=0 
>) based on what they develop as part of their class activities.

Students will be required to program in Python, Java, or C++. It is not necessary to know all three programming languages, but students must be proficient in at least one of these languages.

This course helps student accomplish the following objectives:
•     Understand current challenges in computer game AI;
•     Learn classic and state-of-the-art AI algorithms for game agents;
•     Analyze existing game AI algorithms;
•     Run hands-on experiments on simulated computer game tournaments;
•     Develop a report on the research and development of game AI in this class;
•     Identify potential topics for a potential HTC/M.Sc./Ph.D. degree project, thesis, or dissertation.

Prerequisites for CS4900: CS 3560 or equivalent courses.
Prerequisites for CS5900: None.
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