Nate Derbinsky

34 papers A* 11A 2C 2Journal 7Unranked 11
YearRankTypeTitle / Venue / Authors
2025 — conf
Addressing Challenges in Teaching-Track Faculty Promotion.
SIGCSE (2)
Christine Alvarado, Nate Derbinsky, Sarah Heckman, Manuel A. Pérez-Quiñones, Harini Ramaprasad, Mark Sherriff
2024 — conf
Interviewing the Teaching Faculty Hiring Process.
SIGCSE (2)
Geoffrey Challen, Victoria Dean, Nate Derbinsky, Matt X. Wang, Jacqueline Smith
2022 — conf
Using domain knowledge in coevolution and reinforcement learning to simulate a logistics enterprise.
GECCO Companion
Ying Zhao, Erik Hemberg, Nate Derbinsky, Gabino Mata, Una-May O'Reilly
2021 — conf
Simulating a logistics enterprise using an asymmetrical wargame simulation with soar reinforcement learning and coevolutionary algorithms.
GECCO Companion
Ying Zhao, Erik Hemberg, Nate Derbinsky, Gabino Mata, Una-May O'Reilly
2019 A* conf
Model AI Assignments 2019.
AAAI
Todd W. Neller, Raja Sooriamurthi, Michael Guerzhoy, Lisa Zhang, Paul G. Talaga, Christopher Archibald, Adam Summerville, Joseph C. Osborn, Cinjon Resnick, Avital Oliver, Surya Bhupatiraju, Kumar Krishna Agrawal, Nate Derbinsky, Elena Strange, Marion Neumann, Jonathan Chen, Zac Christensen, Michael Wollowski, Oscar Youngquist
2018 A* conf
Model AI Assignments 2018.
AAAI
Todd W. Neller, Zack Butler, Nate Derbinsky, Heidi Furey, Fred Martin, Michael Guerzhoy, Ariel Anders, Joshua Eckroth
2017 A* conf
Cornhole: A Widely-Accessible AI Robotics Task.
AAAI
Nate Derbinsky, Tyler M. Frasca
2017 C conf
Reinforcement Learning for Modeling Large-Scale Cognitive Reasoning.
KEOD
Ying Zhao, Emily Mooren, Nate Derbinsky
2017 A conf
Sustainable Methods for Impactful Service Learning in Computer Science (Abstract Only).
SIGCSE
Nate Derbinsky, Durga Suresh
2016 A* conf
A Comparison of Supervised Learning Algorithms for Telerobotic Control Using Electromyography Signals.
AAAI
Tyler M. Frasca, Antonio G. Sestito, Craig Versek, Douglas E. Dow, Barry C. Husowitz, Nate Derbinsky
2016 A* conf
Model AI Assignments 2016.
AAAI
Todd W. Neller, Laura E. Brown, James B. Marshall, Lisa Torrey, Nate Derbinsky, Andrew A. Ward, Thomas E. Allen, Judy Goldsmith, Nahom Muluneh
2016 — conf
Testing Fine-Grained Parallelism for the ADMM on a Factor-Graph.
IPDPS Workshops
Ning Hao, AmirReza Oghbaee, Mohammad Rostami, Nate Derbinsky, José Bento
2016 J jnl
Testing fine-grained parallelism for the ADMM on a factor-graph.
CoRR
Ning Hao, AmirReza Oghbaee, Mohammad Rostami, Nate Derbinsky, José Bento
2015 A* conf
Proximal Operators for Multi-Agent Path Planning.
AAAI
José Bento, Nate Derbinsky, Charles Mathy, Jonathan S. Yedidia
2015 J jnl
Proximal operators for multi-agent path planning.
CoRR
José Bento, Nate Derbinsky, Charles Mathy, Jonathan S. Yedidia
2015 A* conf
The Boundary Forest Algorithm for Online Supervised and Unsupervised Learning.
AAAI
Charles Mathy, Nate Derbinsky, José Bento, Jonathan Rosenthal, Jonathan S. Yedidia
2015 J jnl
The Boundary Forest Algorithm for Online Supervised and Unsupervised Learning.
CoRR
Charles Mathy, Nate Derbinsky, José Bento, Jonathan Rosenthal, Jonathan S. Yedidia
2013 — conf
A message-passing algorithm for multi-agent trajectory planning.
NIPS
José Bento, Nate Derbinsky, Javier Alonso-Mora, Jonathan S. Yedidia
2013 J jnl
A message-passing algorithm for multi-agent trajectory planning.
CoRR
José Bento, Nate Derbinsky, Javier Alonso-Mora, Jonathan S. Yedidia
2013 J jnl
An Improved Three-Weight Message-Passing Algorithm
CoRR
Nate Derbinsky, José Bento, Veit Elser, Jonathan S. Yedidia
2013 J jnl
Effective and efficient forgetting of learned knowledge in Soar's working and procedural memories.
Cogn. Syst. Res.
Nate Derbinsky, John E. Laird
2013 — conf
Methods for Integrating Knowledge with the Three-Weight Optimization Algorithm for Hybrid Cognitive Processing.
AAAI Fall Symposia
Nate Derbinsky, José Bento, Jonathan S. Yedidia
2013 J jnl
Methods for Integrating Knowledge with the Three-Weight Optimization Algorithm for Hybrid Cognitive Processing.
CoRR
Nate Derbinsky, José Bento, Jonathan S. Yedidia
2012 A* conf
A Multi-Domain Evaluation of Scaling in a General Episodic Memory.
AAAI
Nate Derbinsky, Justin Li, John E. Laird
2012 A conf
Algorithms for scaling in a general episodic memory.
AAMAS
Nate Derbinsky, Justin Li, John E. Laird
2012 — —
Effective and Efficient Memory for Generally Intelligent Agents.
Nate Derbinsky
2012 — conf
Exploring Reinforcement Learning for Mobile Percussive Collaboration.
NIME
Nate Derbinsky, Georg Essl
2012 A* conf
Functional Interactions Between Memory and Recognition Judgments.
AAAI
Justin Li, Nate Derbinsky, John E. Laird
2011 — conf
A Case Study in Integrating Probabilistic Decision Making and Learning in a Symbolic Cognitive Architecture: Soar Plays Dice.
AAAI Fall Symposium: Advances in Cognitive Systems
John Edwin Laird, Nate Derbinsky, Miller Tinkerhess
2011 A* conf
A Functional Analysis of Historical Memory Retrieval Bias in the Word Sense Disambiguation Task.
AAAI
Nate Derbinsky, John E. Laird
2011 — conf
Cognitive Architecture in Mobile Music Interactions.
NIME
Nate Derbinsky, Georg Essl
2011 — conf
Effective and Efficient Management of Soar's Working Memory via Base-Level Activation.
AAAI Fall Symposium: Advances in Cognitive Systems
Nate Derbinsky, John E. Laird
2011 A* conf
Long-Term Declarative Memory for Generally Intelligent Agents.
AAAI
Nate Derbinsky
2009 C conf
Efficiently Implementing Episodic Memory.
ICCBR
Nate Derbinsky, John E. Laird