| Publication |
Sentence |
Publish Date |
Extraction Date |
Species |
| Jieyuan Tan, Xiang Shen, Xiang Zhang, Zhiwei Song, Yiwen Wan. Estimating Reward Function from Medial Prefrontal Cortex Cortical Activity using Inverse Reinforcement Learning. Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference. vol 2022. 2022-09-10. PMID:36086257. |
reinforcement learning (rl)-based brain-machine interfaces (bmis) learn the mapping from neural signals to subjects' intention using a reward signal. |
2022-09-10 |
2023-08-14 |
human |
| Jieyuan Tan, Xiang Shen, Xiang Zhang, Zhiwei Song, Yiwen Wan. Estimating Reward Function from Medial Prefrontal Cortex Cortical Activity using Inverse Reinforcement Learning. Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference. vol 2022. 2022-09-10. PMID:36086257. |
such an internal reward information is validated by checking whether it can guide the training of the rl decoder to complete movement task. |
2022-09-10 |
2023-08-14 |
human |
| Jieyuan Tan, Xiang Shen, Xiang Zhang, Zhiwei Song, Yiwen Wan. Estimating Reward Function from Medial Prefrontal Cortex Cortical Activity using Inverse Reinforcement Learning. Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference. vol 2022. 2022-09-10. PMID:36086257. |
compared with the rl decoder trained with the external reward, our approach achieves a similar decoding performance. |
2022-09-10 |
2023-08-14 |
human |
| Armando Ordonez, Oscar Mauricio Caicedo, William Villota, Angela Rodriguez-Vivas, Nelson L S da Fonsec. Model-Based Reinforcement Learning with Automated Planning for Network Management. Sensors (Basel, Switzerland). vol 22. issue 16. 2022-08-26. PMID:36016062. |
our experiments evaluate on a simulated environment evidence that the combination proposed improves model-free rl but demonstrates lower performance than deep rl regarding the reward and convergence time metrics. |
2022-08-26 |
2023-08-14 |
Not clear |
| Bo-Wei Chen, Shih-Hung Yang, Chao-Hung Kuo, Jia-Wei Chen, Yu-Chun Lo, Yun-Ting Kuo, Yi-Chen Lin, Hao-Cheng Chang, Sheng-Huang Lin, Xiao Yu, Boyi Qu, Shuan-Chu Vina Ro, Hsin-Yi Lai, You-Yin Che. Neuro-Inspired Reinforcement Learning to Improve Trajectory Prediction in Reward-Guided Behavior. International journal of neural systems. 2022-08-22. PMID:35989578. |
the computational method of reinforcement learning (rl) has been widely used to investigate spatial navigation, which in turn has been increasingly used to study rodent learning associated with the reward. |
2022-08-22 |
2023-08-14 |
Not clear |
| Bo-Wei Chen, Shih-Hung Yang, Chao-Hung Kuo, Jia-Wei Chen, Yu-Chun Lo, Yun-Ting Kuo, Yi-Chen Lin, Hao-Cheng Chang, Sheng-Huang Lin, Xiao Yu, Boyi Qu, Shuan-Chu Vina Ro, Hsin-Yi Lai, You-Yin Che. Neuro-Inspired Reinforcement Learning to Improve Trajectory Prediction in Reward-Guided Behavior. International journal of neural systems. 2022-08-22. PMID:35989578. |
the rewards in rl are used for discovering a desired behavior through the integration of two streams of neural activity: trial-and-error interactions with the external environment to achieve a goal, and the intrinsic motivation primarily driven by brain reward system to accelerate learning. |
2022-08-22 |
2023-08-14 |
Not clear |
| Bo-Wei Chen, Shih-Hung Yang, Chao-Hung Kuo, Jia-Wei Chen, Yu-Chun Lo, Yun-Ting Kuo, Yi-Chen Lin, Hao-Cheng Chang, Sheng-Huang Lin, Xiao Yu, Boyi Qu, Shuan-Chu Vina Ro, Hsin-Yi Lai, You-Yin Che. Neuro-Inspired Reinforcement Learning to Improve Trajectory Prediction in Reward-Guided Behavior. International journal of neural systems. 2022-08-22. PMID:35989578. |
recognizing the potential benefit of the neural representation of this reward design for novel rl architectures, we propose a rl algorithm based on [formula: see text]-learning with a perspective on biomimetics (neuro-inspired rl) to decode rodent movement trajectories. |
2022-08-22 |
2023-08-14 |
Not clear |
| Kenway Loui. Asymmetric and adaptive reward coding via normalized reinforcement learning. PLoS computational biology. vol 18. issue 7. 2022-07-21. PMID:35862443. |
while standard rl assumes linear reward functions, reward-related neural activity is a saturating, nonlinear function of reward; however, the computational and behavioral implications of nonlinear rl are unknown. |
2022-07-21 |
2023-08-14 |
Not clear |
| Giovanni Granato, Emilio Cartoni, Federico Da Rold, Andrea Mattera, Gianluca Baldassarr. Integrating unsupervised and reinforcement learning in human categorical perception: A computational model. PloS one. vol 17. issue 5. 2022-05-10. PMID:35536843. |
despite the fact that experimental studies and computational models suggest that this tuning is influenced by task-independent effects (e.g., based on hebbian and unsupervised learning, ul) and task-dependent effects (e.g., based on reward signals and reinforcement learning, rl), no model studies the ul/rl interaction during the emergence of categorical perception. |
2022-05-10 |
2023-08-13 |
human |
| Weiyi Zhang, Yancao Jiang, Fasih Ud Din Farrukh, Chun Zhang, Debing Zhang, Guangqi Wan. LORM: a novel reinforcement learning framework for biped gait control. PeerJ. Computer science. vol 8. 2022-05-02. PMID:35494792. |
the rl environment was finely crafted for optimal performance, including the pruning of state space and action space, reward shaping, and design of episode criterion. |
2022-05-02 |
2023-08-13 |
Not clear |
| Bunyodbek Ibrokhimov, Young-Joo Kim, Sanggil Kan. Biased Pressure: Cyclic Reinforcement Learning Model for Intelligent Traffic Signal Control. Sensors (Basel, Switzerland). vol 22. issue 7. 2022-04-12. PMID:35408431. |
however, most of existing state-of-the-art rl methods use complex state definition and reward functions and/or neglect the real-world constraints such as cyclic phase order and minimum/maximum duration for each traffic phase. |
2022-04-12 |
2023-08-13 |
Not clear |
| Amy R Zou, Daniela E Muñoz Lopez, Sheri L Johnson, Anne G E Collin. Impulsivity Relates to Multi-Trial Choice Strategy in Probabilistic Reversal Learning. Frontiers in psychiatry. vol 13. 2022-04-01. PMID:35360119. |
reinforcement learning (rl) relies on the ability to integrate reward or punishment outcomes to make good decisions, and has recently been shown to often recruit executive function; as such, it is unsurprising that impulsivity has been studied in the context of rl. |
2022-04-01 |
2023-08-13 |
Not clear |
| Mohammad Salimibeni, Arash Mohammadi, Parvin Malekzadeh, Konstantinos N Platanioti. Multi-Agent Reinforcement Learning via Adaptive Kalman Temporal Difference and Successor Representation. Sensors (Basel, Switzerland). vol 22. issue 4. 2022-02-26. PMID:35214293. |
generally speaking, conventional model-based (mb) or model-free (mf) rl algorithms are not directly applicable to the marl problems due to utilization of a fixed reward model for learning the underlying value function. |
2022-02-26 |
2023-08-13 |
Not clear |
| Sepideh Heydari, Clay B Holroy. Pain feedback interferes with reward positivity production. Psychophysiology. 2022-02-19. PMID:35182391. |
the reinforcement learning (rl) theory of the reward positivity (rewp) proposes that rewp indexes a reward prediction error (rpe) signal processed in the anterior cingulate cortex (acc). |
2022-02-19 |
2023-08-13 |
human |
| Yanjun Shi, Yuanzhuo Liu, Yuhan Qi, Qiaomei Ha. A Control Method with Reinforcement Learning for Urban Un-Signalized Intersection in Hybrid Traffic Environment. Sensors (Basel, Switzerland). vol 22. issue 3. 2022-02-15. PMID:35161523. |
then, state, action and reward of rl are designed according to urban unsignalized intersection problem. |
2022-02-15 |
2023-08-13 |
human |
| Max Doody, Maaike M H Van Swieten, Sanjay G Manoha. Model-based learning retrospectively updates model-free values. Scientific reports. vol 12. issue 1. 2022-02-12. PMID:35149713. |
model-free learning is a simple rl process in which a value is associated with actions, whereas model-based learning relies on the formation of internal models of the environment to maximise reward. |
2022-02-12 |
2023-08-13 |
human |
| Kenji Yamaguchi, Yoshitomo Maeda, Takeshi Sawada, Yusuke Iino, Mio Tajiri, Ryosuke Nakazato, Shin Ishii, Haruo Kasai, Sho Yagishit. A behavioural correlate of the synaptic eligibility trace in the nucleus accumbens. Scientific reports. vol 12. issue 1. 2022-02-05. PMID:35121769. |
reinforcement learning (rl) theory and recent brain slice studies explain the delayed reward action such that synaptic activities triggered by sensorimotor events leave a synaptic eligibility trace for 1 s. |
2022-02-05 |
2023-08-13 |
Not clear |
| Sandeep Sathyanandan Nair, Vignayanandam Ravindernath Muddapu, V Srinivasa Chakravarth. A Multiscale, Systems-Level, Neuropharmacological Model of Cortico-Basal Ganglia System for Arm Reaching Under Normal, Parkinsonian, and Levodopa Medication Conditions. Frontiers in computational neuroscience. vol 15. 2022-01-20. PMID:35046787. |
there is a modelling tradition that links dopamine to reward and uses reinforcement learning (rl) concepts to model the basal ganglia. |
2022-01-20 |
2023-08-13 |
Not clear |
| Mohammad Reza Bonyadi, Rui Wang, Maryam Ziae. Self-Punishment and Reward Backfill for Deep Q-Learning. IEEE transactions on neural networks and learning systems. vol PP. 2022-01-18. PMID:35041613. |
reinforcement learning (rl) agents learn by encouraging behaviors, which maximizes their total reward, usually provided by the environment. |
2022-01-18 |
2023-08-13 |
Not clear |
| Mohammad Reza Bonyadi, Rui Wang, Maryam Ziae. Self-Punishment and Reward Backfill for Deep Q-Learning. IEEE transactions on neural networks and learning systems. vol PP. 2022-01-18. PMID:35041613. |
we prove that, under certain assumptions and regardless of the rl algorithm used, these two strategies maintain the order of policies in the space of all possible policies in terms of their total reward and, by extension, maintain the optimal policy. |
2022-01-18 |
2023-08-13 |
Not clear |