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ResearchWe work in genetic algorithms, evolutionary computing, and their applications to Artificial Intelligence, Machine Learning, and Optimization

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Potential Field Based Co-Evolution of Micro in StarCraft-II

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Emergency Rescue


Welcome to the Evolutionary Computing Systems Lab (ECSL) directed by Dr. Sushil J. Louis. ECSL is hosted by the Computer Science Department of the University of Nevada-Reno. We investigate systems that use genetic algorithm (GA) search to evolve AI for RTS games, to evolve, interaction design and directed autonomy for large numbers of heterogenous simulated and real-world agents, and to augment machine learning and deep learning approaches. We have worked on new techniques for machine learning using Case-Injected Genetic AlgoRithms (CIGAR), new techniques for playing to learn to play computer games, and new techniques for evolving Real-Time Strategy (RTS) game micro and macro . Check out a few of our current projects below.

At a Glance

Bridge Inspection Simulator

We use an iterative software engineering process to investigate and build a series of Simulation Training And Control System known as (STACS). STACS will be used for both operator training and operator control of robot inspection teams consisting of multiple robots.

3D RTS micro

Can we use Potential field based Co-Evolution to develop good micro techniques in StarCraft-II?

RoR Intelligent Tutoring System

Can we effectively use an Intelligent Tutoring System (ITS) to perform knowledge tracing in order to accurately estimate a student's level of knowledge? RoR-ITS is aimed at teaching midshipmen about different ship types, target angle, and identifying ship activities by looking at ship navigation lights at night.

Meet the Crew

Meet the Alumni