| Publication |
Sentence |
Publish Date |
Extraction Date |
Species |
| Enrique Adrian Villarrubia-Martin, Luis Rodriguez-Benitez, Luis Jimenez-Linares, David Muñoz-Valero, Jun Li. A Hybrid Online Off-Policy Reinforcement Learning Agent Framework Supported by Transformers. International journal of neural systems. 2023-10-19. PMID:37857407. |
reinforcement learning (rl) is a powerful technique that allows agents to learn optimal decision-making policies through interactions with an environment. |
2023-10-19 |
2023-11-08 |
Not clear |
| Arslan Musaddiq, Tobias Olsson, Fredrik Ahlgre. Reinforcement-Learning-Based Routing and Resource Management for Internet of Things Environments: Theoretical Perspective and Challenges. Sensors (Basel, Switzerland). vol 23. issue 19. 2023-10-14. PMID:37837093. |
meanwhile, reinforcement learning (rl) has proven to be one of the most effective solutions for decision making. |
2023-10-14 |
2023-10-15 |
Not clear |
| Arslan Musaddiq, Tobias Olsson, Fredrik Ahlgre. Reinforcement-Learning-Based Routing and Resource Management for Internet of Things Environments: Theoretical Perspective and Challenges. Sensors (Basel, Switzerland). vol 23. issue 19. 2023-10-14. PMID:37837093. |
rl holds significant potential for its application in iot device's communication-related decision making, with the goal of improving performance. |
2023-10-14 |
2023-10-15 |
Not clear |
| Sharon M Noh, Umesh K Singla, Ilana J Bennett, Aaron M Bornstei. Memory precision and age differentially predict the use of decision-making strategies across the lifespan. Scientific reports. vol 13. issue 1. 2023-10-09. PMID:37813942. |
recent work has proposed memory sampling as a specific computational role for memory in decision-making, alongside well-studied mechanisms of reinforcement learning (rl). |
2023-10-09 |
2023-10-15 |
human |
| Toby Wise, Kara Emery, Angela Radulesc. Naturalistic reinforcement learning. Trends in cognitive sciences. 2023-09-30. PMID:37777463. |
human cognitive computational neuroscience has sought to exploit reinforcement learning (rl) as a framework within which to explain human decision-making, often focusing on constrained, artificial experimental tasks. |
2023-09-30 |
2023-10-07 |
human |
| Jung In Kim, Young Jae Lee, Jongkook Heo, Jinhyeok Park, Jaehoon Kim, Sae Rin Lim, Jinyong Jeong, Seoung Bum Ki. Sample-efficient multi-agent reinforcement learning with masked reconstruction. PloS one. vol 18. issue 9. 2023-09-14. PMID:37708154. |
deep reinforcement learning (drl) is a powerful approach that combines reinforcement learning (rl) and deep learning to address complex decision-making problems in high-dimensional environments. |
2023-09-14 |
2023-10-07 |
Not clear |
| Erik M Elster, Ruth Pauli, Sarah Baumann, Stephane A De Brito, Graeme Fairchild, Christine M Freitag, Kerstin Konrad, Veit Roessner, Inti A Brazil, Patricia L Lockwood, Gregor Kohl. Impaired Punishment Learning in Conduct Disorder. Journal of the American Academy of Child and Adolescent Psychiatry. 2023-07-06. PMID:37414274. |
conduct disorder (cd) has been associated with deficits in the use of punishment to guide reinforcement learning (rl) and decision making. |
2023-07-06 |
2023-08-14 |
Not clear |
| Tianmeng Hu, Biao Luo, Chunhua Yang, Tingwen Huan. MO-MIX: Multi-Objective Multi-Agent Cooperative Decision-Making With Deep Reinforcement Learning. IEEE transactions on pattern analysis and machine intelligence. vol PP. 2023-06-07. PMID:37285257. |
deep reinforcement learning (rl) has been applied extensively to solve complex decision-making problems. |
2023-06-07 |
2023-08-14 |
Not clear |
| Nour Ben Hassen, Francisco Molins, Mónica Paz, Miguel-Ángel Serran. Later stages of acute stress impair reinforcement-learning and feedback sensitivity in decision making. Biological psychology. 2023-05-13. PMID:37178755. |
the value-plus-preservation (vpp) rl computational model was used to extract decision-making components. |
2023-05-13 |
2023-08-14 |
human |
| Milena Rmus, Mingjian He, Beth Baribault, Edward G Walsh, Elena K Festa, Anne G E Collins, Matthew R Nassa. Age-related differences in prefrontal glutamate are associated with increased working memory decay that gives the appearance of learning deficits. eLife. vol 12. 2023-04-18. PMID:37070807. |
distinguishing between these hypotheses has been challenging because either rl or wm could be used to facilitate successful decision making in typical laboratory tasks. |
2023-04-18 |
2023-08-14 |
Not clear |
| Bo Lyu, Shengbo Wang, Shiping Wen, Kaibo Shi, Yin Yang, Lingfang Zeng, Tingwen Huan. AutoGMap: Learning to Map Large-Scale Sparse Graphs on Memristive Crossbars. IEEE transactions on neural networks and learning systems. vol PP. 2023-04-18. PMID:37071512. |
this work proposes the dynamic sparsity-aware mapping scheme generating method that models the problem with a sequential decision-making model, and optimizes it by reinforcement learning (rl) algorithm (reinforce). |
2023-04-18 |
2023-08-14 |
Not clear |
| Chang Liu, Lixin Tang, Chenche Zha. A Novel Dynamic Operation Optimization Method Based on Multiobjective Deep Reinforcement Learning for Steelmaking Process. IEEE transactions on neural networks and learning systems. vol PP. 2023-04-07. PMID:37027625. |
then, an energy-informed restricted boltzmann machine method with physical interpretability is developed to construct the actor and critic networks in reinforcement learning (rl) for dynamic decision-making operations. |
2023-04-07 |
2023-08-14 |
Not clear |
| Ying Meng, Fengyuan Shi, Lixin Tang, Defeng Su. Improvement of Reinforcement Learning With Supermodularity. IEEE transactions on neural networks and learning systems. vol PP. 2023-04-07. PMID:37027690. |
reinforcement learning (rl) is a promising approach to tackling learning and decision-making problems in a dynamic environment. |
2023-04-07 |
2023-08-14 |
Not clear |
| Sang Ho Oh, Min Ki Jeong, Hyung Chan Kim, Jongyoul Par. Applying Reinforcement Learning for Enhanced Cybersecurity against Adversarial Simulation. Sensors (Basel, Switzerland). vol 23. issue 6. 2023-03-30. PMID:36991711. |
reinforcement learning (rl) has shown great potential in solving complex decision-making problems in various domains, including cybersecurity. |
2023-03-30 |
2023-08-14 |
Not clear |
| Alana Jaskir, Michael J Fran. On the normative advantages of dopamine and striatal opponency for learning and choice. eLife. vol 12. 2023-03-22. PMID:36946371. |
the basal ganglia (bg) contribute to reinforcement learning (rl) and decision making, but unlike artificial rl agents, it relies on complex circuitry and dynamic dopamine modulaton of opponent striatal pathways to do so. |
2023-03-22 |
2023-08-14 |
Not clear |
| Chaoqiong Fan, Li Yao, Jiacai Zhang, Zonglei Zhen, Xia W. Advanced Reinforcement Learning and Its Connections with Brain Neuroscience. Research (Washington, D.C.). vol 6. 2023-03-20. PMID:36939448. |
in particular, knowledge from the neurobiology and neuropsychology of the brain revolutionized the development of reinforcement learning (rl) by providing novel interpretable mechanisms of how the brain achieves intelligent and efficient decision making. |
2023-03-20 |
2023-08-14 |
Not clear |
| Yan Du, Samrat Chatterjee, Arnab Bhattacharya, Ashutosh Dutta, Mahantesh Halappanava. Role of reinforcement learning for risk-based robust control of cyber-physical energy systems. Risk analysis : an official publication of the Society for Risk Analysis. 2023-02-06. PMID:36746175. |
emergence of data-driven techniques for decision making under uncertainty, such as reinforcement learning (rl), have led to promising advances for addressing sequential decision-making problems for risk-based robust cps-e control. |
2023-02-06 |
2023-08-14 |
Not clear |
| Muazzam Maqsood, Sadaf Yasmin, Saira Gillani, Farhan Aadil, Irfan Mehmood, Seungmin Rho, Sang-Soo Ye. An autonomous decision-making framework for gait recognition systems against adversarial attack using reinforcement learning. ISA transactions. 2022-12-09. PMID:36494214. |
we leveraged the vulnerabilities and decision-making abilities of the dl model in gait-based autonomous surveillance systems when attackers have no access to underlying model gradients/structures using a patch-based black-box adversarial attack with reinforcement learning (rl). |
2022-12-09 |
2023-08-14 |
Not clear |
| Markus Böck, Julien Malle, Daniel Pasterk, Hrvoje Kukina, Ramin Hasani, Clemens Heitzinge. Superhuman performance on sepsis MIMIC-III data by distributional reinforcement learning. PloS one. vol 17. issue 11. 2022-11-03. PMID:36327195. |
we demonstrate a suitable method that combines data imputation by a knn model using a custom distance with state representation by discretization using clustering, and that enables superhuman decision-making using speedy q-learning in the framework of distributional rl. |
2022-11-03 |
2023-08-14 |
Not clear |
| Benjamin Ribba, Dominic Stefan Bräm, Paul Gabriel Baverel, Richard Wilson Pec. Model enhanced reinforcement learning to enable precision dosing: A theoretical case study with dosing of propofol. CPT: pharmacometrics & systems pharmacology. 2022-09-30. PMID:36177959. |
reinforcement learning (rl) holds promise in its ability to integrate multidimensional data in an adaptive process built toward efficient decision making centered on sustainable value creation. |
2022-09-30 |
2023-08-14 |
Not clear |