| Publication |
Sentence |
Publish Date |
Extraction Date |
Species |
| Tristan Shah, Linwei Zhuo, Peter Lai, Amaris De La Rosa-Moreno, Feruza Amirkulova, Peter Gerstof. Reinforcement learning applied to metamaterial design. The Journal of the Acoustical Society of America. vol 150. issue 1. 2021-08-03. PMID:34340495. |
as each adjustment is made, the rl agent receives a reward negatively proportional to the root mean square of the tscs across a range of wavenumbers. |
2021-08-03 |
2023-08-13 |
Not clear |
| Hadar Levi-Aharoni, Naftali Tishb. The value-complexity trade-off for reinforcement learning based brain-computer interfaces. Journal of neural engineering. vol 17. issue 6. 2021-06-25. PMID:33586668. |
one of the recent developments in the field of brain-computer interfaces (bci) is the reinforcement learning (rl) based bci paradigm, which uses neural error responses as the reward feedback on the agent's action. |
2021-06-25 |
2023-08-13 |
Not clear |
| Sheng Lian, Zhiming Luo, Cheng Feng, Shaozi Li, Shuo L. APRIL: Anatomical prior-guided reinforcement learning for accurate carotid lumen diameter and intima-media thickness measurement. Medical image analysis. vol 71. 2021-06-25. PMID:33789178. |
in this study, we propose the anatomical prior-guided reinforcement learning model (april), which innovatively formulate the measurement of cald & cimt as an rl problem and dynamically incorporate anatomical prior (ap) into the system through a novel reward. |
2021-06-25 |
2023-08-13 |
human |
| Xiang Shen, Xiang Zhang, Yifan Huang, Shuhang Chen, Yiwen Wan. Task Learning Over Multi-Day Recording via Internally Rewarded Reinforcement Learning Based Brain Machine Interfaces. IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society. vol 28. issue 12. 2021-06-24. PMID:33232240. |
previous reinforcement learning (rl)-based decoders interpret the mapping between neural activity and movements using the external reward for well-trained subjects, and have not investigated the task learning procedure. |
2021-06-24 |
2023-08-13 |
human |
| Zachary B Millman, Keith Gallagher, Caroline Demro, Jason Schiffman, Gloria M Reeves, James M Gold, Pamela J Rakhshan Rouhakhtar, John Fitzgerald, Nicole D Andorko, Samantha Redman, Robert W Buchanan, Laura M Rowland, James A Walt. Evidence of reward system dysfunction in youth at clinical high-risk for psychosis from two event-related fMRI paradigms. Schizophrenia research. vol 226. 2021-06-17. PMID:30995969. |
abnormal reward processing is thought to play an important role in the development of psychosis, but relatively few studies have examined reward prediction errors, reinforcement learning (rl), and the reward circuitry that subserves these interconnected processes among individuals at clinical high-risk (chr) for the disorder. |
2021-06-17 |
2023-08-13 |
human |
| Zachary B Millman, Keith Gallagher, Caroline Demro, Jason Schiffman, Gloria M Reeves, James M Gold, Pamela J Rakhshan Rouhakhtar, John Fitzgerald, Nicole D Andorko, Samantha Redman, Robert W Buchanan, Laura M Rowland, James A Walt. Evidence of reward system dysfunction in youth at clinical high-risk for psychosis from two event-related fMRI paradigms. Schizophrenia research. vol 226. 2021-06-17. PMID:30995969. |
our results provide evidence for rl deficits and abnormal prediction error signaling in the brain's reward circuitry among individuals at chr, while also suggesting that reward motivation may be relatively preserved at this stage in development. |
2021-06-17 |
2023-08-13 |
human |
| Zezhi Sui, Zhiqiang Pu, Jianqiang Yi, Shiguang W. Formation Control With Collision Avoidance Through Deep Reinforcement Learning Using Model-Guided Demonstration. IEEE transactions on neural networks and learning systems. vol 32. issue 6. 2021-06-03. PMID:32673195. |
in the rl stage, a compound reward function is presented to guide the training. |
2021-06-03 |
2023-08-13 |
Not clear |
| Jose M Ceballos, Andrea Stocco, Chantel S Pra. The Role of Basal Ganglia Reinforcement Learning in Lexical Ambiguity Resolution. Topics in cognitive science. vol 12. issue 1. 2021-05-17. PMID:32023006. |
individual differences in task performance were then related to indices of basal ganglia rl, which were used to group subjects into three learning styles: (a) choosers who learn by seeking high reward probability stimuli; (b) avoiders, who learn by avoiding low reward probability stimuli; and (c) balanced participants, whose learning reflects equal contributions of choose and avoid processes. |
2021-05-17 |
2023-08-13 |
human |
| Andrew J Roebuck, Lei An, Wendie N Marks, Ninglei Sun, Terrance P Snutch, John G Howlan. Cognitive Impairments in Touchscreen-based Visual Discrimination and Reversal Learning in Genetic Absence Epilepsy Rats from Strasbourg. Neuroscience. vol 430. 2021-05-14. PMID:32017953. |
deficits in vd and rl were not associated with differences in correct or incorrect response latency, or reward collection latency, suggesting impairments are not due to alterations in locomotor activity or motivation. |
2021-05-14 |
2023-08-13 |
rat |
| Changyin Sun, Wenzhang Liu, Lu Don. Reinforcement Learning With Task Decomposition for Cooperative Multiagent Systems. IEEE transactions on neural networks and learning systems. vol 32. issue 5. 2021-05-04. PMID:32554331. |
the target for a single-agent rl system is represented by its scalar reward signals. |
2021-05-04 |
2023-08-13 |
Not clear |
| Changyin Sun, Wenzhang Liu, Lu Don. Reinforcement Learning With Task Decomposition for Cooperative Multiagent Systems. IEEE transactions on neural networks and learning systems. vol 32. issue 5. 2021-05-04. PMID:32554331. |
existing multiagent rl algorithms search distributed policies with holistic reward signals directly, making it difficult to obtain an optimal policy for each task. |
2021-05-04 |
2023-08-13 |
Not clear |
| Anh Vu Le, Prabakaran Veerajagadheswar, Phone Thiha Kyaw, Mohan Rajesh Elara, Nguyen Huu Khanh Nha. Coverage Path Planning Using Reinforcement Learning-Based TSP for hTetran-A Polyabolo-Inspired Self-Reconfigurable Tiling Robot. Sensors (Basel, Switzerland). vol 21. issue 8. 2021-04-30. PMID:33916995. |
this structure simultaneously produces robot shapes and sequential trajectories whilst maximizing the reward of the trained reinforcement learning (rl) model within the predefined polyabolo-based tileset. |
2021-04-30 |
2023-08-13 |
Not clear |
| Chao Yu, Guoqi Ren, Yinzhao Don. Supervised-actor-critic reinforcement learning for intelligent mechanical ventilation and sedative dosing in intensive care units. BMC medical informatics and decision making. vol 20. issue Suppl 3. 2021-02-15. PMID:32646412. |
however, since the goal of traditional rl algorithms is to maximize a long-term reward function, exploration in the learning process may have a fatal impact on the patient. |
2021-02-15 |
2023-08-13 |
Not clear |
| Christoph Grebner, Hans Matter, Alleyn T Plowright, Gerhard Hessle. Automated De Novo Design in Medicinal Chemistry: Which Types of Chemistry Does a Generative Neural Network Learn? Journal of medicinal chemistry. vol 63. issue 16. 2020-12-08. PMID:32134646. |
first, different chemical spaces were used as training sets for reinforcement learning (rl) in combination with different reward functions. |
2020-12-08 |
2023-08-13 |
Not clear |
| Zhenshan Bing, Christian Lemke, Fabric O Morin, Zhuangyi Jiang, Long Cheng, Kai Huang, Alois Knol. Perception-Action Coupling Target Tracking Control for a Snake Robot via Reinforcement Learning. Frontiers in neurorobotics. vol 14. 2020-11-17. PMID:33192441. |
with a novel customized reward function, our rl controller is trained in a dynamically changing track scenario. |
2020-11-17 |
2023-08-13 |
Not clear |
| Xiang Shen, Xiang Zhang, Yifan Huang, Shuhang Chen, Yiwen Wan. Reinforcement Learning based Decoding Using Internal Reward for Time Delayed Task in Brain Machine Interfaces. Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference. vol 2020. 2020-10-23. PMID:33018722. |
reinforcement learning (rl) algorithm interprets neural signals into movement intentions with the guidance of the reward in brain-machine interfaces (bmis). |
2020-10-23 |
2023-08-13 |
human |
| Xiang Shen, Xiang Zhang, Yifan Huang, Shuhang Chen, Yiwen Wan. Reinforcement Learning based Decoding Using Internal Reward for Time Delayed Task in Brain Machine Interfaces. Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference. vol 2020. 2020-10-23. PMID:33018722. |
current rl algorithms generally work for the tasks with immediate rewards delivery, and lack of efficiency in delayed reward task. |
2020-10-23 |
2023-08-13 |
human |
| Marco A Huertas, Sarah E Schwettmann, Harel Z Shouva. The Role of Multiple Neuromodulators in Reinforcement Learning That Is Based on Competition between Eligibility Traces. Frontiers in synaptic neuroscience. vol 8. 2020-10-01. PMID:28018206. |
reinforcement learning (rl) refers to the algorithms used by biological or artificial systems to learn how to maximize reward or avoid negative outcomes based on past experiences. |
2020-10-01 |
2023-08-13 |
Not clear |
| Stephane Doncieux, David Filliat, Natalia Díaz-Rodríguez, Timothy Hospedales, Richard Duro, Alexandre Coninx, Diederik M Roijers, Benoît Girard, Nicolas Perrin, Olivier Sigau. Open-Ended Learning: A Conceptual Framework Based on Representational Redescription. Frontiers in neurorobotics. vol 12. 2020-09-30. PMID:30319388. |
reinforcement learning (rl) aims at building a policy that maximizes a task-related reward within a given domain. |
2020-09-30 |
2023-08-13 |
Not clear |
| Stephane Doncieux, David Filliat, Natalia Díaz-Rodríguez, Timothy Hospedales, Richard Duro, Alexandre Coninx, Diederik M Roijers, Benoît Girard, Nicolas Perrin, Olivier Sigau. Open-Ended Learning: A Conceptual Framework Based on Representational Redescription. Frontiers in neurorobotics. vol 12. 2020-09-30. PMID:30319388. |
when the domain is known, i.e., when its states, actions and reward are defined, markov decision processes (mdps) provide a convenient theoretical framework to formalize rl. |
2020-09-30 |
2023-08-13 |
Not clear |