| Approximate value iteration with complex returns by bounding R Wright, L Yu, S Loscalzo US Patent 10,839,302, 2020 | 59 | 2020 |
| Evolutionary tile coding: An automated state abstraction algorithm for reinforcement learning S Lin, R Wright Workshops at the Twenty-Fourth AAAI Conference on Artificial Intelligence, 2010 | 34 | 2010 |
| Shorter path constraints for the resource constrained shortest path problem T Gellermann, M Sellmann, R Wright Integration of AI and OR Techniques in Constraint Programming for …, 2005 | 24 | 2005 |
| Insights from BB-MAS--A Large Dataset for Typing, Gait and Swipes of the Same Person on Desktop, Tablet and Phone AK Belman, L Wang, SS Iyengar, P Sniatala, R Wright, R Dora, J Baldwin, ... arXiv preprint arXiv:1912.02736, 2019 | 23 | 2019 |
| Diverse exploration for fast and safe policy improvement A Cohen, L Yu, R Wright Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018 | 18 | 2018 |
| Cost-based filtering for shorter path constraints M Sellmann, T Gellermann, R Wright Constraints 12, 207-238, 2007 | 18 | 2007 |
| Novgrid: A flexible grid world for evaluating agent response to novelty J Balloch, Z Lin, M Hussain, A Srinivas, R Wright, X Peng, J Kim, M Riedl arXiv preprint arXiv:2203.12117, 2022 | 16 | 2022 |
| Embedded Incremental Feature Selection for Reinforcement Learning R Wright, S Loscalzo, L Yu International Conference on Agents and Artificial Intelligence, 263-268, 2011 | 16 | 2011 |
| Sample aware embedded feature selection for reinforcement learning S Loscalzo, R Wright, K Acunto, L Yu Proceedings of the 14th annual conference on Genetic and evolutionary …, 2012 | 13 | 2012 |
| Predictive feature selection for genetic policy search S Loscalzo, R Wright, L Yu Autonomous Agents and Multi-Agent Systems 29, 754-786, 2015 | 11 | 2015 |
| Exploiting multi-step sample trajectories for approximate value iteration R Wright, S Loscalzo, P Dexter, L Yu Machine Learning and Knowledge Discovery in Databases: European Conference …, 2013 | 10 | 2013 |
| State Aggregation for Reinforcement Learning using Neuroevolution R Wright, N Gemelli International Conference on Agents and Artificial Intelligence, 45-52, 2009 | 10 | 2009 |
| Shared multi-keyboard and bilingual datasets to support keystroke dynamics research AA Wahab, D Hou, M Banavar, S Schuckers, K Eaton, J Baldwin, R Wright Proceedings of the Twelfth ACM Conference on Data and Application Security …, 2022 | 8 | 2022 |
| Beyond speech: Generalizing d-vectors for biometric verification J Baldwin, R Burnham, A Meyer, R Dora, R Wright Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 842-849, 2019 | 6 | 2019 |
| A rationality-based modeling for coalition support JC Oh, N Gemelli, R Wright Fourth International Conference on Hybrid Intelligent Systems (HIS'04), 172-177, 2004 | 6 | 2004 |
| Neuro-Symbolic World Models for Adapting to Open World Novelty J Balloch, Z Lin, R Wright, X Peng, M Hussain, A Srinivas, J Kim, MO Riedl arXiv preprint arXiv:2301.06294, 2023 | 5 | 2023 |
| CFQI: Fitted Q-Iteration with Complex Returns. RW Wright, X Qiao, L Yu, S Loscalzo AAMAS, 163-170, 2015 | 5 | 2015 |
| Automatic methods for continuous state space abstraction S Loscalzo, R Wright Workshops at the Twenty-Fourth AAAI Conference on Artificial Intelligence, 2010 | 5 | 2010 |
| Progressive mining of transition dynamics for autonomous control S Loscalzo, R Wright, K Acunto, L Yu 2012 IEEE 12th International Conference on Data Mining, 990-995, 2012 | 4 | 2012 |
| Adaptive state space abstraction using neuroevolution R Wright, N Gemelli Agents and Artificial Intelligence: International Conference, ICAART 2009 …, 2010 | 4 | 2010 |
Lei YuDepartment of Computer Science, Binghamton UniversityDirección de correo verificada de cs.binghamton.edu
