Nick Sohre

PhD Candidate, University of Minnesota CSE

My goal is to help empower humanity by creating more social forms of artificial intelligence that incorporate an understanding of human activity into their behavior. My research interests include Machine Learning and Data-Driven AI, Graphics, and VR.

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Recent Publications

Implicit Crowds: Optimization Integrator for Robust Crowd Simulation (image missing)
SIGGRAPH 2017 Full Paper

Implicit Crowds: Optimization Integrator for Robust Crowd Simulation

Large multi-agent systems involve interactions that are anticipatory in nature. We propose a simple and effective optimization-based integration scheme for the implicit integration of such systems...

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Evaluating Collision Avoidance Effects on Discomfort in Virtual Environments (image missing)
IEEE VR 2017 VHCIE Workshop Paper

Evaluating Collision Avoidance Effects on Discomfort in Virtual Environments

Here, we explore the role collision avoidance between virtual agents and the VR user plays on experiences in an immersive virtual environment. When Collision avoidance was used, we found...

Full Report (PDF)
Data Driven Sokoban Puzzle Generation with MCTS (image missing)
AIIDE 2016 Full Paper (Best Student Paper Award)

Data Driven Sokoban Puzzle Generation with MCTS

In this work, we propose a Monte Carlo Tree Search (MCTS) based approach to procedurally generate Sokoban puzzles. Our method generates puzzles through simulated game play, guaranteeing solvability...

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Research

My work seeks to combine state of the art AI with real world data to understand and solve complex problems

Education

University of Minnesota

Dordt College

Experience

My professional experience includes teaching, software engineering, and development on both large and small scale projects.

University of Minnesota

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