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ORCIDNicholas R. Waytowich
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2020 – today
- 2024
[c32]Devin White, Mingkang Wu, Ellen R. Novoseller, Vernon J. Lawhern, Nicholas R. Waytowich, Yongcan Cao
:
Rating-Based Reinforcement Learning. AAAI 2024: 10207-10215- [c31]Vinicius G. Goecks, Nicholas R. Waytowich:
COA-GPT: Generative Pre-Trained Transformers for Accelerated Course of Action Development in Military Operations. ICMCIS 2024: 1-10 - [c30]Anna Madison, Ellen R. Novoseller, Vinicius G. Goecks, Benjamin T. Files, Nicholas R. Waytowich, Alfred Yu, Vernon J. Lawhern, Steven Thurman, Christopher Kelshaw, Kaleb McDowell:
Scalable Interactive Machine Learning for Future Command and Control. ICMCIS 2024: 1-10 - [i38]Sean Kulinski, Nicholas R. Waytowich, James Z. Hare, David I. Inouye:
StarCraftImage: A Dataset For Prototyping Spatial Reasoning Methods For Multi-Agent Environments. CoRR abs/2401.04290 (2024) - [i37]Vinicius G. Goecks, Nicholas R. Waytowich:
COA-GPT: Generative Pre-trained Transformers for Accelerated Course of Action Development in Military Operations. CoRR abs/2402.01786 (2024) - [i36]Anna Madison, Ellen R. Novoseller, Vinicius G. Goecks, Benjamin T. Files, Nicholas R. Waytowich, Alfred Yu, Vernon J. Lawhern, Steven Thurman, Christopher Kelshaw, Kaleb McDowell:
Scalable Interactive Machine Learning for Future Command and Control. CoRR abs/2402.06501 (2024) - [i35]Ahaan Dabholkar, James Z. Hare, Mark R. Mittrick, John T. Richardson, Nicholas R. Waytowich, Priya Narayanan, Saurabh Bagchi:
Adversarial Attacks on Reinforcement Learning Agents for Command and Control. CoRR abs/2405.01693 (2024) - [i34]Nicholas R. Waytowich, Devin White, MD Sunbeam, Vinicius G. Goecks:
Atari-GPT: Investigating the Capabilities of Multimodal Large Language Models as Low-Level Policies for Atari Games. CoRR abs/2408.15950 (2024) - 2023
- [c29]Sean Kulinski, Nicholas R. Waytowich, James Z. Hare, David I. Inouye:
StarCraftImage: A Dataset For Prototyping Spatial Reasoning Methods For Multi-Agent Environments. CVPR 2023: 22004-22013 - [i33]Stephanie Milani, Anssi Kanervisto, Karolis Ramanauskas, Sander Schulhoff, Brandon Houghton, Sharada P. Mohanty, Byron Galbraith, Ke Chen, Yan Song, Tianze Zhou, Bingquan Yu, He Liu, Kai Guan, Yujing Hu, Tangjie Lv, Federico Malato, Florian Leopold, Amogh Raut, Ville Hautamäki, Andrew Melnik, Shu Ishida, João F. Henriques, Robert Klassert, Walter Laurito, Ellen R. Novoseller, Vinicius G. Goecks, Nicholas R. Waytowich, David Watkins, Josh Miller, Rohin Shah:
Towards Solving Fuzzy Tasks with Human Feedback: A Retrospective of the MineRL BASALT 2022 Competition. CoRR abs/2303.13512 (2023) - [i32]Prashant Ganesh, J. Humberto Ramos, Vinicius G. Goecks, Jared Paquet, Matthew Longmire, Nicholas R. Waytowich, Kevin M. Brink:
Learning Flight Control Systems from Human Demonstrations and Real-Time Uncertainty-Informed Interventions. CoRR abs/2305.00929 (2023) - [i31]Vinicius G. Goecks, Nicholas R. Waytowich:
DisasterResponseGPT: Large Language Models for Accelerated Plan of Action Development in Disaster Response Scenarios. CoRR abs/2306.17271 (2023) - [i30]Ellen R. Novoseller, Vinicius G. Goecks, David Watkins, Josh Miller, Nicholas R. Waytowich:
DIP-RL: Demonstration-Inferred Preference Learning in Minecraft. CoRR abs/2307.12158 (2023) - [i29]Devin White, Mingkang Wu, Ellen R. Novoseller, Vernon J. Lawhern, Nicholas R. Waytowich, Yongcan Cao:
Rating-based Reinforcement Learning. CoRR abs/2307.16348 (2023) - 2022
- [j10]Aidin Shiri, Arnab Neelim Mazumder, Bharat Prakash, Houman Homayoun, Nicholas R. Waytowich, Tinoosh Mohsenin:
A Hardware Accelerator for Language-Guided Reinforcement Learning. IEEE Des. Test 39(3): 37-44 (2022) - [j9]Aidin Shiri, Mozhgan Navardi, Tejaswini Manjunath, Nicholas R. Waytowich, Tinoosh Mohsenin:
Efficient Language-Guided Reinforcement Learning for Resource-Constrained Autonomous Systems. IEEE Micro 42(6): 107-114 (2022) - [j8]Brian Cesar-Tondreau, Garrett Warnell, Kevin Kochersberger, Nicholas R. Waytowich:
Towards Fully Autonomous Negative Obstacle Traversal via Imitation Learning Based Control. Robotics 11(4): 67 (2022) - [j7]Aidin Shiri, Uttej Kallakuri, Hasib-Al Rashid, Bharat Prakash, Nicholas R. Waytowich, Tim Oates, Tinoosh Mohsenin:
E2HRL: An Energy-efficient Hardware Accelerator for Hierarchical Deep Reinforcement Learning. ACM Trans. Design Autom. Electr. Syst. 27(5): 45:1-45:19 (2022) - [c28]Vinicius G. Goecks, Nicholas R. Waytowich, David Watkins-Valls, Bharat Prakash:
Combining Learning From Human Feedback and Knowledge Engineering to Solve Hierarchical Tasks in Minecraft. AAAI Spring Symposium: MAKE 2022 - [c27]Mozhgan Navardi, Aidin Shiri, Edward Humes, Nicholas R. Waytowich, Tinoosh Mohsenin:
An Optimization Framework for Efficient Vision-Based Autonomous Drone Navigation. AICAS 2022: 304-307 - [c26]Indrajeet Ghosh, Avijoy Chakma, Sreenivasan Ramasamy Ramamurthy, Nirmalya Roy, Nicholas R. Waytowich:
PerMTL: A Multi-Task Learning Framework for Skilled Human Performance Assessment. ICMLA 2022: 37-44 - [c25]David Watkins-Valls, Peter K. Allen, Henrique Maia, Madhavan Seshadri, Jonathan Sanabria, Nicholas R. Waytowich, Jacob Varley:
Mobile Manipulation Leveraging Multiple Views. IROS 2022: 4585-4592 - [c24]Kasthuri Jayarajah, Aryya Gangopadhyay, Nicholas R. Waytowich:
TagTeam: Towards wearable-assisted, implicit guidance for human-drone teams. SmartWear@MobiCom 2022: 13-18 - [i28]Rohin Shah, Steven H. Wang, Cody Wild, Stephanie Milani, Anssi Kanervisto, Vinicius G. Goecks, Nicholas R. Waytowich, David Watkins-Valls, Bharat Prakash, Edmund Mills, Divyansh Garg, Alexander Fries, Alexandra Souly, Jun Shern Chan, Daniel del Castillo, Tom Lieberum:
Retrospective on the 2021 BASALT Competition on Learning from Human Feedback. CoRR abs/2204.07123 (2022) - [i27]Nicholas R. Waytowich, James Z. Hare, Vinicius G. Goecks, Mark R. Mittrick, John T. Richardson, Anjon Basak, Derrik E. Asher:
Learning to Guide Multiple Heterogeneous Actors from a Single Human Demonstration via Automatic Curriculum Learning in StarCraft II. CoRR abs/2205.05784 (2022) - [i26]Kasthuri Jayarajah, Aryya Gangopadhyay, Nicholas R. Waytowich:
TagTeam: Towards Wearable-Assisted, Implicit Guidance for Human-Drone Teams. CoRR abs/2208.05410 (2022) - [i25]David Watkins-Valls, Peter E. Allen, Krzysztof Choromanski, Jacob Varley, Nicholas R. Waytowich:
Multiple View Performers for Shape Completion. CoRR abs/2209.06291 (2022) - [i24]Bharat Prakash, Nicholas R. Waytowich, Tim Oates, Tinoosh Mohsenin:
Towards an Interpretable Hierarchical Agent Framework using Semantic Goals. CoRR abs/2210.08412 (2022) - 2021
- [j6]Brian Cesar-Tondreau, Garrett Warnell, Ethan Stump, Kevin Kochersberger, Nicholas R. Waytowich:
Improving Autonomous Robotic Navigation Using Imitation Learning. Frontiers Robotics AI 8: 627730 (2021) - [j5]Mohit Khatwani, Hasib-Al Rashid, Hirenkumar Paneliya, Mark Horton, Nicholas R. Waytowich, W. David Hairston, Tinoosh Mohsenin:
A Flexible Multichannel EEG Artifact Identification Processor using Depthwise-Separable Convolutional Neural Networks. ACM J. Emerg. Technol. Comput. Syst. 17(2): 23:1-23:21 (2021) - [j4]Nitheesh Kumar Manjunath, Aidin Shiri, Morteza Hosseini, Bharat Prakash, Nicholas R. Waytowich, Tinoosh Mohsenin:
An Energy Efficient EdgeAI Autoencoder Accelerator for Reinforcement Learning. IEEE Open J. Circuits Syst. 2: 182-195 (2021) - [c23]Aidin Shiri, Bharat Prakash, Arnab Neelim Mazumder, Nicholas R. Waytowich, Tim Oates, Tinoosh Mohsenin:
An Energy-Efficient Hardware Accelerator for Hierarchical Deep Reinforcement Learning. AICAS 2021: 1-4 - [c22]Stephanie Milani, Anssi Kanervisto, Karolis Ramanauskas, Sander Schulhoff, Brandon Houghton, Sharada P. Mohanty, Byron Galbraith, Ke Chen, Yan Song, Tianze Zhou, Bingquan Yu, He Liu, Kai Guan, Yujing Hu, Tangjie Lv, Federico Malato, Florian Leopold, Amogh Raut, Ville Hautamäki, Andrew Melnik, Shu Ishida, João F. Henriques, Robert Klassert, Walter Laurito, Lucas Cazzonelli, Cedric Kulbach, Nicholas Popovic, Marvin Schweizer, Ellen R. Novoseller, Vinicius G. Goecks, Nicholas R. Waytowich, David Watkins, Josh Miller, Rohin Shah:
Towards Solving Fuzzy Tasks with Human Feedback: A Retrospective of the MineRL BASALT 2022 Competition. NeurIPS (Competition and Demos) 2021: 171-188 - [c21]Rohin Shah, Steven H. Wang, Cody Wild, Stephanie Milani, Anssi Kanervisto, Vinicius G. Goecks, Nicholas R. Waytowich, David Watkins-Valls, Bharat Prakash, Edmund Mills, Divyansh Garg, Alexander Fries, Alexandra Souly, Jun Shern Chan, Daniel del Castillo, Tom Lieberum:
Retrospective on the 2021 MineRL BASALT Competition on Learning from Human Feedback. NeurIPS (Competition and Demos) 2021: 259-272 - [i23]Ritwik Bera, Vinicius G. Goecks, Gregory M. Gremillion, Vernon J. Lawhern, John Valasek, Nicholas R. Waytowich:
Gaze-Informed Multi-Objective Imitation Learning from Human Demonstrations. CoRR abs/2102.13008 (2021) - [i22]David Watkins-Valls, Peter K. Allen, Henrique Maia, Madhavan Seshadri, Jonathan Sanabria, Nicholas R. Waytowich, Jacob Varley:
Mobile Manipulation Leveraging Multiple Views. CoRR abs/2110.00717 (2021) - [i21]Bharat Prakash, Nicholas R. Waytowich, Tim Oates, Tinoosh Mohsenin:
Interactive Hierarchical Guidance using Language. CoRR abs/2110.04649 (2021) - [i20]Vinicius G. Goecks, Nicholas R. Waytowich, Derrik E. Asher, Song Jun Park, Mark R. Mittrick, John T. Richardson, Manuel Vindiola, Anne Logie, Mark Dennison, Theron Trout, Priya Narayanan, Alexander Kott:
On games and simulators as a platform for development of artificial intelligence for command and control. CoRR abs/2110.11305 (2021) - [i19]Bharat Prakash, Nicholas R. Waytowich, Tinoosh Mohsenin, Tim Oates:
Automatic Goal Generation using Dynamical Distance Learning. CoRR abs/2111.04120 (2021) - [i18]Vinicius G. Goecks, Nicholas R. Waytowich, David Watkins, Bharat Prakash:
Combining Learning from Human Feedback and Knowledge Engineering to Solve Hierarchical Tasks in Minecraft. CoRR abs/2112.03482 (2021) - 2020
- [j3]Addison W. Bohannon, Vernon J. Lawhern, Nicholas R. Waytowich, Radu V. Balan:
The Autoregressive Linear Mixture Model: A Time-Series Model for an Instantaneous Mixture of Network Processes. IEEE Trans. Signal Process. 68: 4481-4496 (2020) - [c20]Bharat Prakash, Nicholas R. Waytowich, Ashwinkumar Ganesan, Tim Oates, Tinoosh Mohsenin:
Guiding Safe Reinforcement Learning Policies Using Structured Language Constraints. SafeAI@AAAI 2020: 153-161 - [c19]Ritwik Bera, Vinicius G. Goecks, Gregory M. Gremillion, John Valasek, Nicholas R. Waytowich:
PODNet: A Neural Network for Discovery of Plannable Options. AAAI Spring Symposium: Combining Machine Learning with Knowledge Engineering (1) 2020 - [c18]Vinicius G. Goecks, Gregory M. Gremillion, Vernon J. Lawhern, John Valasek, Nicholas R. Waytowich:
Integrating Behavior Cloning and Reinforcement Learning for Improved Performance in Dense and Sparse Reward Environments. AAMAS 2020: 465-473 - [c17]Divya Ramesh, Anthony Z. Liu, Andres J. Echeverria, Jean Y. Song, Nicholas R. Waytowich, Walter S. Lasecki:
Yesterday's Reward is Today's Punishment: Contrast Effects in Human Feedback to Reinforcement Learning Agents. AAMAS 2020: 1090-1097 - [c16]Aidin Shiri, Arnab Neelim Mazumder, Bharat Prakash, Nitheesh Kumar Manjunath, Houman Homayoun, Avesta Sasan, Nicholas R. Waytowich, Tinoosh Mohsenin:
Energy-Efficient Hardware for Language Guided Reinforcement Learning. ACM Great Lakes Symposium on VLSI 2020: 131-136 - [c15]David Watkins-Valls, Jingxi Xu, Nicholas R. Waytowich, Peter K. Allen:
Learning Your Way Without Map or Compass: Panoramic Target Driven Visual Navigation. IROS 2020: 5816-5823
2010 – 2019
- 2019
- [c14]Vinicius G. Goecks, Gregory M. Gremillion, Vernon J. Lawhern, John Valasek, Nicholas R. Waytowich:
Efficiently Combining Human Demonstrations and Interventions for Safe Training of Autonomous Systems in Real-Time. AAAI 2019: 2462-2470 - [c13]Sunil Gandhi, Tim Oates, Tinoosh Mohsenin, Nicholas R. Waytowich:
Learning Behaviors from a Single Video Demonstration Using Human Feedback. AAMAS 2019: 1970-1972 - [c12]Pawan Lapborisuth, Josef Faller, Jonathan Koss, Nicholas R. Waytowich, Jonathan Touryan, Paul Sajda:
Investigating Evoked EEG Responses to Targets Presented in Virtual Reality. EMBC 2019: 5536-5539 - [c11]Bharat Prakash, Mohit Khatwani, Nicholas R. Waytowich, Tinoosh Mohsenin:
Improving Safety in Reinforcement Learning Using Model-Based Architectures and Human Intervention. FLAIRS 2019: 50-55 - [c10]Bharat Prakash, Mark Horton, Nicholas R. Waytowich, William David Hairston, Tim Oates, Tinoosh Mohsenin:
On the use of Deep Autoencoders for Efficient Embedded Reinforcement Learning. ACM Great Lakes Symposium on VLSI 2019: 507-512 - [c9]Sean L. Barton, Erin G. Zaroukian, Derrik E. Asher, Nicholas R. Waytowich:
Evaluating the Coordination of Agents in Multi-agent Reinforcement Learning. IHSI 2019: 765-770 - [i17]Bharat Prakash, Mohit Khatwani, Nicholas R. Waytowich, Tinoosh Mohsenin:
Improving Safety in Reinforcement Learning Using Model-Based Architectures and Human Intervention. CoRR abs/1903.09328 (2019) - [i16]Bharat Prakash, Mark Horton, Nicholas R. Waytowich, William David Hairston, Tim Oates, Tinoosh Mohsenin:
On the use of Deep Autoencoders for Efficient Embedded Reinforcement Learning. CoRR abs/1903.10404 (2019) - [i15]Nicholas R. Waytowich, Sean L. Barton, Vernon Lawhern, Ethan Stump, Garrett Warnell:
Grounding Natural Language Commands to StarCraft II Game States for Narration-Guided Reinforcement Learning. CoRR abs/1906.02671 (2019) - [i14]Yilun Zhou, Derrik E. Asher, Nicholas R. Waytowich, Julie A. Shah:
On Memory Mechanism in Multi-Agent Reinforcement Learning. CoRR abs/1909.05232 (2019) - [i13]Pietro Pierpaoli, Harish Ravichandar, Nicholas R. Waytowich, Anqi Li, Derrik E. Asher, Magnus Egerstedt:
Inferring and Learning Multi-Robot Policies by Observing an Expert. CoRR abs/1909.07887 (2019) - [i12]David Watkins-Valls, Jingxi Xu, Nicholas R. Waytowich, Peter K. Allen:
Learning Your Way Without Map or Compass: Panoramic Target Driven Visual Navigation. CoRR abs/1909.09295 (2019) - [i11]Sunil Gandhi, Tim Oates, Tinoosh Mohsenin, Nicholas R. Waytowich:
Learning from Observations Using a Single Video Demonstration and Human Feedback. CoRR abs/1909.13392 (2019) - [i10]Vinicius G. Goecks, Gregory M. Gremillion, Vernon J. Lawhern, John Valasek, Nicholas R. Waytowich:
Integrating Behavior Cloning and Reinforcement Learning for Improved Performance in Sparse Reward Environments. CoRR abs/1910.04281 (2019) - [i9]Ritwik Bera, Vinicius G. Goecks, Gregory M. Gremillion, John Valasek, Nicholas R. Waytowich:
PODNet: A Neural Network for Discovery of Plannable Options. CoRR abs/1911.00171 (2019) - [i8]Nicholas R. Waytowich, Sean L. Barton, Vernon Lawhern, Garrett Warnell:
A Narration-based Reward Shaping Approach using Grounded Natural Language Commands. CoRR abs/1911.00497 (2019) - 2018
- [c8]Garrett Warnell, Nicholas R. Waytowich, Vernon Lawhern, Peter Stone:
Deep TAMER: Interactive Agent Shaping in High-Dimensional State Spaces. AAAI 2018: 1545-1554 - [c7]Sean L. Barton, Nicholas R. Waytowich, Derrik E. Asher:
Coordination-driven Learning in Multi-agent Problem Spaces. AAAI Fall Symposium: ALEC 2018: 56-58 - [c6]Mohit Khatwani, Morteza Hosseini, Hirenkumar Paneliya, Tinoosh Mohsenin, W. David Hairston, Nicholas R. Waytowich:
Energy Efficient Convolutional Neural Networks for EEG Artifact Detection. BioCAS 2018: 1-4 - [c5]Sean L. Barton, Nicholas R. Waytowich, Erin G. Zaroukian, Derrik E. Asher:
Measuring Collaborative Emergent Behavior in Multi-agent Reinforcement Learning. IHSED 2018: 422-427 - [i7]Nicholas R. Waytowich, Vernon Lawhern, Javier O. Garcia, Jennifer Cummings, Josef Faller, Paul Sajda, Jean M. Vettel:
Compact Convolutional Neural Networks for Classification of Asynchronous Steady-state Visual Evoked Potentials. CoRR abs/1803.04566 (2018) - [i6]Sean L. Barton, Nicholas R. Waytowich, Erin G. Zaroukian, Derrik E. Asher:
Measuring collaborative emergent behavior in multi-agent reinforcement learning. CoRR abs/1807.08663 (2018) - [i5]Nicholas R. Waytowich, Vinicius G. Goecks, Vernon J. Lawhern:
Cycle-of-Learning for Autonomous Systems from Human Interaction. CoRR abs/1808.09572 (2018) - [i4]Sean L. Barton, Nicholas R. Waytowich, Derrik E. Asher:
Coordination-driven learning in multi-agent problem spaces. CoRR abs/1809.04918 (2018) - [i3]Vinicius G. Goecks, Gregory M. Gremillion, Vernon J. Lawhern, John Valasek, Nicholas R. Waytowich:
Efficiently Combining Human Demonstrations and Interventions for Safe Training of Autonomous Systems in Real-Time. CoRR abs/1810.11545 (2018) - 2017
- [c4]Nicholas R. Waytowich, Dean J. Krusienski:
Development of an extensible SSVEP-BCI software platform and application to wheelchair control. NER 2017: 259-532 - [i2]Garrett Warnell, Nicholas R. Waytowich, Vernon Lawhern, Peter Stone:
Deep TAMER: Interactive Agent Shaping in High-Dimensional State Spaces. CoRR abs/1709.10163 (2017) - 2016
- [j2]Sameer Saproo, Josef Faller, Victor Shih, Paul Sajda, Nicholas R. Waytowich, Addison W. Bohannon, Vernon J. Lawhern, Brent J. Lance, David C. Jangraw:
Cortically Coupled Computing: A New Paradigm for Synergistic Human-Machine Interaction. Computer 49(9): 60-68 (2016) - [j1]Nicholas R. Waytowich, Dean J. Krusienski:
Multiclass Steady-State Visual Evoked Potential Frequency Evaluation Using Chirp-Modulated Stimuli. IEEE Trans. Hum. Mach. Syst. 46(4): 593-600 (2016) - [c3]Addison W. Bohannon, Nicholas R. Waytowich, Vernon J. Lawhern, Brian M. Sadler, Brent J. Lance:
Collaborative image triage with humans and computer vision. SMC 2016: 4046-4051 - [c2]Nicholas R. Waytowich, Josef Faller, Javier O. Garcia, Jean M. Vettel, Paul Sajda:
Unsupervised adaptive transfer learning for Steady-State Visual Evoked Potential brain-computer interfaces. SMC 2016: 4135-4140 - [i1]Vernon J. Lawhern, Amelia J. Solon, Nicholas R. Waytowich, Stephen M. Gordon, Chou P. Hung, Brent J. Lance:
EEGNet: A Compact Convolutional Network for EEG-based Brain-Computer Interfaces. CoRR abs/1611.08024 (2016) - 2011
- [c1]Garett D. Johnson, Nicholas R. Waytowich, Dean J. Krusienski:
The Challenges of Using Scalp-EEG Input Signals for Continuous Device Control. HCI (20) 2011: 525-527
Coauthor Index
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