| Publication |
Sentence |
Publish Date |
Extraction Date |
Species |
| Cameron D Hassall, Greg Hajcak, Olave E Krigolso. The importance of agency in human reward processing. Cognitive, affective & behavioral neuroscience. vol 19. issue 6. 2020-09-28. PMID:31187443. |
for example, the reward positivity-a feedback-sensitive component of the event-related brain potential (erp)-is thought to index an rl prediction error. |
2020-09-28 |
2023-08-13 |
human |
| Amir H Abdi, Benedikt Sagl, Venkata P Srungarapu, Ian Stavness, Eitan Prisman, Purang Abolmaesumi, Sidney Fel. Characterizing Motor Control of Mastication With Soft Actor-Critic. Frontiers in human neuroscience. vol 14. 2020-09-28. PMID:32528267. |
we demonstrate how the model learns more metabolically efficient policies by integrating a force regularization term in the rl reward. |
2020-09-28 |
2023-08-13 |
human |
| Yazhou Hu, Wenxue Wang, Hao Liu, Lianqing Li. Reinforcement Learning Tracking Control for Robotic Manipulator With Kernel-Based Dynamic Model. IEEE transactions on neural networks and learning systems. vol 31. issue 9. 2020-09-02. PMID:31689218. |
in this algorithm, a reward function is defined according to the features of tracking control in order to speed up the learning process, and then an rl tracking controller with a kernel-based transition dynamic model is proposed. |
2020-09-02 |
2023-08-13 |
Not clear |
| Vincent D Costa, Bruno B Averbec. Primate Orbitofrontal Cortex Codes Information Relevant for Managing Explore-Exploit Tradeoffs. The Journal of neuroscience : the official journal of the Society for Neuroscience. vol 40. issue 12. 2020-08-28. PMID:32060169. |
reinforcement learning (rl) refers to the behavioral process of learning to obtain reward and avoid punishment. |
2020-08-28 |
2023-08-13 |
monkey |
| Davide Gheza, Jasmina Bakic, Chris Baeken, Rudi De Raedt, Gilles Pourtoi. Abnormal approach-related motivation but spared reinforcement learning in MDD: Evidence from fronto-midline Theta oscillations and frontal Alpha asymmetry. Cognitive, affective & behavioral neuroscience. vol 19. issue 3. 2020-07-17. PMID:30675690. |
major depression is characterized by abnormal reward processing and reinforcement learning (rl). |
2020-07-17 |
2023-08-13 |
human |
| Marco P Lehmann, He A Xu, Vasiliki Liakoni, Michael H Herzog, Wulfram Gerstner, Kerstin Preuschof. One-shot learning and behavioral eligibility traces in sequential decision making. eLife. vol 8. 2020-05-04. PMID:31709980. |
reinforcement learning (rl) theory suggests two classes of algorithms solving this credit assignment problem: in classic temporal-difference learning, earlier actions receive reward information only after multiple repetitions of the task, whereas models with eligibility traces reinforce entire sequences of actions from a single experience (one-shot). |
2020-05-04 |
2023-08-13 |
Not clear |
| Junmo An, Taruna Yadav, John P Hessburg, Joseph T Franci. Reward Expectation Modulates Local Field Potentials, Spiking Activity and Spike-Field Coherence in the Primary Motor Cortex. eNeuro. vol 6. issue 3. 2020-03-30. PMID:31171607. |
reward modulation (m1) could be exploited in developing an autonomously updating brain-computer interface (bci) based on a reinforcement learning (rl) architecture. |
2020-03-30 |
2023-08-13 |
Not clear |
| Chao Yu, Jiming Liu, Hongyi Zha. Inverse reinforcement learning for intelligent mechanical ventilation and sedative dosing in intensive care units. BMC medical informatics and decision making. vol 19. issue Suppl 2. 2020-01-14. PMID:30961594. |
this paper applies inverse rl in inferring the reward functions that clinicians have in mind during their decisions on weaning of mechanical ventilation and sedative dosing in intensive care units (icus). |
2020-01-14 |
2023-08-13 |
Not clear |
| Roselinde H Kaiser, Michael T Treadway, Dustin W Wooten, Poornima Kumar, Franziska Goer, Laura Murray, Miranda Beltzer, Pia Pechtel, Alexis Whitton, Andrew L Cohen, Nathaniel M Alpert, Georges El Fakhri, Marc D Normandin, Diego A Pizzagall. Frontostriatal and Dopamine Markers of Individual Differences in Reinforcement Learning: A Multi-modal Investigation. Cerebral cortex (New York, N.Y. : 1991). vol 28. issue 12. 2019-11-12. PMID:29121332. |
prior studies have shown that dopamine (da) functioning in frontostriatal circuits supports reinforcement learning (rl), as phasic da activity in ventral striatum signals unexpected reward and may drive coordinated activity of striatal and orbitofrontal regions that support updating of action plans. |
2019-11-12 |
2023-08-13 |
Not clear |
| Don Murdoch, Ruidong Chen, Jesse H Goldber. Place preference and vocal learning rely on distinct reinforcers in songbirds. Scientific reports. vol 8. issue 1. 2019-10-01. PMID:29712967. |
in reinforcement learning (rl) agents are typically tasked with maximizing a single objective function such as reward. |
2019-10-01 |
2023-08-13 |
Not clear |
| Qi Zhou, You-Wei Chen, Shuyi Shen, Yiming Kong, Mu Xu, Junwen Zhang, Gee-Kung Chan. Proactive real-time interference avoidance in a 5G millimeter-wave over fiber mobile fronthaul using SARSA reinforcement learning. Optics letters. vol 44. issue 17. 2019-09-06. PMID:31465398. |
the rl consists of three core factors, including state, action, and reward. |
2019-09-06 |
2023-08-13 |
Not clear |
| Matthew P H Gardner, Geoffrey Schoenbaum, Samuel J Gershma. Rethinking dopamine as generalized prediction error. Proceedings. Biological sciences. vol 285. issue 1891. 2019-08-16. PMID:30464063. |
by signalling errors in both sensory and reward predictions, dopamine supports a form of rl that lies between model-based and model-free algorithms. |
2019-08-16 |
2023-08-13 |
Not clear |
| Jie Pan, Xuesong Wang, Yuhu Cheng, Qiang Yu, Jie Pan, Xuesong Wang, Yuhu Cheng, Qiang Yu, Qiang Yu, Yuhu Cheng, Jie Pan, Xuesong Wan. Multisource Transfer Double DQN Based on Actor Learning. IEEE transactions on neural networks and learning systems. vol 29. issue 6. 2019-07-25. PMID:29771674. |
deep reinforcement learning (rl) comprehensively uses the psychological mechanisms of "trial and error" and "reward and punishment" in rl as well as powerful feature expression and nonlinear mapping in deep learning. |
2019-07-25 |
2023-08-13 |
Not clear |
| Su Kyoung Kim, Elsa Andrea Kirchner, Arne Stefes, Frank Kirchne. Intrinsic interactive reinforcement learning - Using error-related potentials for real world human-robot interaction. Scientific reports. vol 7. issue 1. 2019-07-11. PMID:29242555. |
explicit human feedback during robot rl is advantageous, since an explicit reward function can be easily adapted. |
2019-07-11 |
2023-08-13 |
human |
| Benedicte M Babayan, Naoshige Uchida, Samuel J Gershma. Belief state representation in the dopamine system. Nature communications. vol 9. issue 1. 2018-11-27. PMID:29760401. |
dopamine activity is a non-monotonic function of reward size, consistent with rl models operating on belief states. |
2018-11-27 |
2023-08-13 |
mouse |
| Kathleen M Jagodnik, Philip S Thomas, Antonie J van den Bogert, Michael S Branicky, Robert F Kirsc. Training an Actor-Critic Reinforcement Learning Controller for Arm Movement Using Human-Generated Rewards. IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society. vol 25. issue 10. 2018-06-25. PMID:28475063. |
reinforcement learning (rl) is a control strategy that can incorporate human reward signals as inputs to allow human users to shape controller behavior. |
2018-06-25 |
2023-08-13 |
human |
| Sven Collette, Wolfgang M Pauli, Peter Bossaerts, John O'Dohert. Neural computations underlying inverse reinforcement learning in the human brain. eLife. vol 6. 2018-06-12. PMID:29083301. |
using formal model comparison, we found that participants implemented inverse rl as opposed to a simple imitation strategy, in which the actions of the other agent are copied instead of inferring the underlying reward structure of the decision problem. |
2018-06-12 |
2023-08-13 |
human |
| Brian Lau, Tiago Monteiro, Joseph J Pato. The many worlds hypothesis of dopamine prediction error: implications of a parallel circuit architecture in the basal ganglia. Current opinion in neurobiology. vol 46. 2018-06-11. PMID:28985550. |
computational models of reinforcement learning (rl) strive to produce behavior that maximises reward, and thus allow software or robots to behave adaptively [1]. |
2018-06-11 |
2023-08-13 |
Not clear |
| Ying Wang, Ning Ma, Xiaosong He, Nan Li, Zhengde Wei, Lizhuang Yang, Rujing Zha, Long Han, Xiaoming Li, Daren Zhang, Ying Liu, Xiaochu Zhan. Neural substrates of updating the prediction through prediction error during decision making. NeuroImage. vol 157. 2018-05-28. PMID:28536046. |
learning of prediction error (pe), including reward pe and risk pe, is crucial for updating the prediction in reinforcement learning (rl). |
2018-05-28 |
2023-08-13 |
Not clear |
| Deanna M Barch, Cameron S Carter, James M Gold, Sheri L Johnson, Ann M Kring, Angus W MacDonald, Diego A Pizzagalli, J Daniel Ragland, Steven M Silverstein, Milton E Straus. Explicit and implicit reinforcement learning across the psychosis spectrum. Journal of abnormal psychology. vol 126. issue 5. 2018-01-26. PMID:28406662. |
an important aspect of motivational function is reinforcement learning (rl), including implicit (i.e., outside of conscious awareness) and explicit (i.e., including explicit representations about potential reward associations) learning, as well as both positive reinforcement (learning about actions that lead to reward) and punishment (learning to avoid actions that lead to loss). |
2018-01-26 |
2023-08-13 |
Not clear |