Embodied dyadic interaction increases complexity of neural dynamics: A minimal agent-based simulation model M Candadai, M Setzler, EJ Izquierdo, T Froese Frontiers in psychology 10, 540, 2019 | 34 | 2019 |
Hierarchical policy learning is sensitive to goal space design Z Dwiel, M Candadai, M Phielipp, AK Bansal arXiv preprint arXiv:1905.01537, 2019 | 19 | 2019 |
infotheory: A c++/python package for multivariate information theoretic analysis M Candadai, EJ Izquierdo Journal of Open Source Software, 2019 | 15 | 2019 |
Reinforcement learning beyond the Bellman equation: Exploring critic objectives using evolution A Leite, M Candadai, EJ Izquierdo Artificial Life Conference Proceedings 32, 441-449, 2020 | 14 | 2020 |
Sources of predictive information in dynamical neural networks M Candadai, EJ Izquierdo Scientific reports 10 (1), 16901, 2020 | 12 | 2020 |
Interaction between evolution and learning in nk fitness landscapes G Todd, M Candadai, EJ Izquierdo Artificial Life Conference Proceedings 32, 761-767, 2020 | 12 | 2020 |
Evolution and analysis of embodied spiking neural networks reveals task-specific clusters of effective networks MC Vasu, EJ Izquierdo Proceedings of the Genetic and Evolutionary Computation Conference, 75-82, 2017 | 9* | 2017 |
Information bottleneck in control tasks with recurrent spiking neural networks MC Vasu, EJ Izquierdo Artificial Neural Networks and Machine Learning–ICANN 2017: 26th …, 2017 | 7 | 2017 |
ANSWER: An unsupervised attractor network method for detecting salient words in text corpora M Candadai, A Vanarase, M Mei, AA Minai International Joint Conference on Neural Networks (IJCNN), 2015, 1-8, 2015 | 7 | 2015 |
Multifunctionality in embodied agents: Three levels of neural reuse M Candadai, EJ Izquierdo Proceedings of the 40th Cognitive Science Conference, 2018 | 6 | 2018 |
On Training Flexible Robots using Deep Reinforcement Learning Z Dwiel, M Candadai, M Phielipp IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS …, 2019 | 4 | 2019 |
Neural reuse in multifunctional neural networks for control tasks LV Benson, M Candadai, EJ Izquierdo Artificial Life Conference Proceedings 32, 210-218, 2020 | 3 | 2020 |
Machine learning logic-based adjustment techniques for robots A Lonsberry, A Lonsberry, NA Gard, MC Vasu, E Schwenker US Patent App. 18/056,443, 2023 | 2 | 2023 |
Autonomous welding robots AJ Lonsberry, AG Lonsberry, A Nima, C Bunker, CFB QUIROZ, MC Vasu US Patent App. 18/360,751, 2024 | 1 | 2024 |
Autonomous welding robots AJ Lonsberry, AG Lonsberry, NA Gard, C Bunker, CFB QUIROZ, MC Vasu US Patent 11,648,683, 2023 | 1 | 2023 |
Information theoretic analysis of computational models as a tool to understand the neural basis of behaviors M Candadai arXiv preprint arXiv:2106.05186, 2021 | 1 | 2021 |
REAL TIME FEEDBACK AND DYNAMIC ADJUSTMENT FOR WELDING ROBOTS AJ Lonsberry, D Desantis, MC Vasu US Patent App. 18/818,355, 2024 | | 2024 |
AUTONOMOUS WELDING ROBOTS AJ Lonsberry, AG Lonsberry, N Ajam Gard, C Bunker, CF Benitez Quiroz, ... US Patent App. 18/790,732, 2024 | | 2024 |
Real time feedback and dynamic adjustment for welding robots AJ Lonsberry, D Desantis, MC Vasu US Patent 12,109,709, 2024 | | 2024 |
Autonomous welding robots AJ Lonsberry, AG Lonsberry, A Nima, C Bunker, CFB QUIROZ, MC Vasu US Patent 12,070,867, 2024 | | 2024 |