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Published in Carleton University, 2016
This paper examines prior implementations of finite state behaviors in the context of AI-applied digital games and proposes player augmentation improvements through the use of “fast” reinforcement learning coupled with “slow” policy planning.
Recommended citation: Sullivan, Z. (2016). "Behavioral Valence - Modeling Cohesive Actions to Augment Human Interaction." Carleton University. 1(1). https://www.zacharysullivan.net/_files/ugd/35ba71_a1ebfb97db174e1b9d93f1920353452b.pdf
Published in Medium, 2020
This paper discusses the potential to further enhance the speed and efficiency of clinical COVID-19 tests and quality assurance procedures through the application of Digital Twin modeling.
Published in Harvard DASH, 2023
This thesis discuesses AERO, an adaptive multi-variable optimizing control framework for AAVs.
Recommended citation: Sullivan, Zachary. 2023. AERO: A Neo-Darwinian Approach to Time-Energy Optimal Behavioral Robotics. Masters thesis, Harvard University Division of Continuing Education. https://dash.harvard.edu/handle/1/37374997
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In 2013, I had the opportunity to present my contribution to Carleton University’s research work on evaluating the applicability of the InMoov 3D printed prosthetic robotic arm at the Ottawa Maker Faire.
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“With video game designers and developers from around the world in Ottawa this week for a conference, analysts want them to take a deeper look at sexism in video games to make them more inclusive.” - CBC News
Undergraduate course, University 1, Department, 2014
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Workshop, University 1, Department, 2015
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