CDRL: A Reinforcement Learning Framework Inspired by Cerebellar Circuits and Dendritic Computational Strategies
Fuente:
arXiv
Saved in:
| Main Authors: | Zhang, Sibo, Jing, Rui, Lv, Liangfu, Zhang, Jian, Zang, Yunliang |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Seemingly Redundant Modules Enhance Robust Odor Learning in Fruit Flies
by: Li, Haiyang, et al.
Published: (2025)
by: Li, Haiyang, et al.
Published: (2025)
A Low Latency Adaptive Coding Spiking Framework for Deep Reinforcement Learning
by: Qin, Lang, et al.
Published: (2022)
by: Qin, Lang, et al.
Published: (2022)
Structure as Computation: Developmental Generation of Minimal Neural Circuits
by: Zhou, Duan
Published: (2026)
by: Zhou, Duan
Published: (2026)
Evolution Strategies at Scale: LLM Fine-Tuning Beyond Reinforcement Learning
by: Qiu, Xin, et al.
Published: (2025)
by: Qiu, Xin, et al.
Published: (2025)
SpikeRL: A Scalable and Energy-efficient Framework for Deep Spiking Reinforcement Learning
by: Tahmid, Tokey, et al.
Published: (2025)
by: Tahmid, Tokey, et al.
Published: (2025)
Applications of Nature-Inspired Metaheuristic Algorithms for Tackling Optimization Problems Across Disciplines
by: Cui, Elvis Han, et al.
Published: (2023)
by: Cui, Elvis Han, et al.
Published: (2023)
Probabilistic Neural Circuits
by: Martires, Pedro Zuidberg Dos
Published: (2024)
by: Martires, Pedro Zuidberg Dos
Published: (2024)
LLS: Local Learning Rule for Deep Neural Networks Inspired by Neural Activity Synchronization
by: Apolinario, Marco Paul E., et al.
Published: (2024)
by: Apolinario, Marco Paul E., et al.
Published: (2024)
Learning and Improving Backgammon Strategy
by: Galperin, Gregory R.
Published: (2025)
by: Galperin, Gregory R.
Published: (2025)
Dynamic Reinforcement Learning for Actors
by: Shibata, Katsunari
Published: (2025)
by: Shibata, Katsunari
Published: (2025)
CLASSP: a Biologically-Inspired Approach to Continual Learning through Adjustment Suppression and Sparsity Promotion
by: Ludwig, Oswaldo
Published: (2024)
by: Ludwig, Oswaldo
Published: (2024)
Reinforcement Learning-assisted Evolutionary Algorithm: A Survey and Research Opportunities
by: Song, Yanjie, et al.
Published: (2023)
by: Song, Yanjie, et al.
Published: (2023)
Unveiling the Potential of Spiking Dynamics in Graph Representation Learning through Spatial-Temporal Normalization and Coding Strategies
by: Xu, Mingkun, et al.
Published: (2024)
by: Xu, Mingkun, et al.
Published: (2024)
Evolving Reservoirs for Meta Reinforcement Learning
by: Léger, Corentin, et al.
Published: (2023)
by: Léger, Corentin, et al.
Published: (2023)
Hierarchical Residuals Exploit Brain-Inspired Compositionality
by: López, Francisco M., et al.
Published: (2025)
by: López, Francisco M., et al.
Published: (2025)
Heuristically Adaptive Diffusion-Model Evolutionary Strategy
by: Hartl, Benedikt, et al.
Published: (2024)
by: Hartl, Benedikt, et al.
Published: (2024)
Deep Reinforcement Learning with Spiking Q-learning
by: Chen, Ding, et al.
Published: (2022)
by: Chen, Ding, et al.
Published: (2022)
QF-tuner: Breaking Tradition in Reinforcement Learning
by: Jumaah, Mahmood A., et al.
Published: (2024)
by: Jumaah, Mahmood A., et al.
Published: (2024)
Learning Heuristics for Transit Network Design and Improvement with Deep Reinforcement Learning
by: Holliday, Andrew, et al.
Published: (2024)
by: Holliday, Andrew, et al.
Published: (2024)
Frequency and Generalisation of Periodic Activation Functions in Reinforcement Learning
by: Mavor-Parker, Augustine N., et al.
Published: (2024)
by: Mavor-Parker, Augustine N., et al.
Published: (2024)
Reinforced In-Context Black-Box Optimization
by: Song, Lei, et al.
Published: (2024)
by: Song, Lei, et al.
Published: (2024)
Synaptic Activation and Dual Liquid Dynamics for Interpretable Bio-Inspired Models
by: Farsang, Mónika, et al.
Published: (2026)
by: Farsang, Mónika, et al.
Published: (2026)
Generalized Population-Based Training for Hyperparameter Optimization in Reinforcement Learning
by: Bai, Hui, et al.
Published: (2024)
by: Bai, Hui, et al.
Published: (2024)
Unveiling the Decision-Making Process in Reinforcement Learning with Genetic Programming
by: Eberhardinger, Manuel, et al.
Published: (2024)
by: Eberhardinger, Manuel, et al.
Published: (2024)
On the Temperature of Machine Learning Systems
by: Zhang, Dong
Published: (2024)
by: Zhang, Dong
Published: (2024)
Scalability of Reinforcement Learning Methods for Dispatching in Semiconductor Frontend Fabs: A Comparison of Open-Source Models with Real Industry Datasets
by: Stöckermann, Patrick, et al.
Published: (2025)
by: Stöckermann, Patrick, et al.
Published: (2025)
Memoria: Resolving Fateful Forgetting Problem through Human-Inspired Memory Architecture
by: Park, Sangjun, et al.
Published: (2023)
by: Park, Sangjun, et al.
Published: (2023)
REACT: Revealing Evolutionary Action Consequence Trajectories for Interpretable Reinforcement Learning
by: Altmann, Philipp, et al.
Published: (2024)
by: Altmann, Philipp, et al.
Published: (2024)
Fully Spiking Actor Network with Intra-layer Connections for Reinforcement Learning
by: Chen, Ding, et al.
Published: (2024)
by: Chen, Ding, et al.
Published: (2024)
Beyond Single-Model Optimization: Preserving Plasticity in Continual Reinforcement Learning
by: Lillo, Lute, et al.
Published: (2026)
by: Lillo, Lute, et al.
Published: (2026)
Continual Learning with Neuromorphic Computing: Foundations, Methods, and Emerging Applications
by: Minhas, Mishal Fatima, et al.
Published: (2024)
by: Minhas, Mishal Fatima, et al.
Published: (2024)
QSLM: A Performance- and Memory-aware Quantization Framework with Tiered Search Strategy for Spike-driven Language Models
by: Putra, Rachmad Vidya Wicaksana, et al.
Published: (2026)
by: Putra, Rachmad Vidya Wicaksana, et al.
Published: (2026)
Izhikevich-Inspired Temporal Dynamics for Enhancing Privacy, Efficiency, and Transferability in Spiking Neural Networks
by: Moshruba, Ayana, et al.
Published: (2025)
by: Moshruba, Ayana, et al.
Published: (2025)
Brain-Inspired Spiking Neural Networks for Industrial Fault Diagnosis: A Survey, Challenges, and Opportunities
by: Wang, Huan, et al.
Published: (2023)
by: Wang, Huan, et al.
Published: (2023)
HyperGraphX: Graph Transductive Learning with Hyperdimensional Computing and Message Passing
by: Cong, Guojing, et al.
Published: (2025)
by: Cong, Guojing, et al.
Published: (2025)
SPEAR: Structured Pruning for Spiking Neural Networks via Synaptic Operation Estimation and Reinforcement Learning
by: Xie, Hui, et al.
Published: (2025)
by: Xie, Hui, et al.
Published: (2025)
A Novel Reservoir Computing Framework for Chaotic Time Series Prediction Using Time Delay Embedding and Random Fourier Features
by: Laha, S. K.
Published: (2025)
by: Laha, S. K.
Published: (2025)
LLM-Meta-SR: In-Context Learning for Evolving Selection Operators in Symbolic Regression
by: Zhang, Hengzhe, et al.
Published: (2025)
by: Zhang, Hengzhe, et al.
Published: (2025)
Enhancing Graph Representation Learning with Attention-Driven Spiking Neural Networks
by: Yin, Huifeng, et al.
Published: (2024)
by: Yin, Huifeng, et al.
Published: (2024)
Experience Replay Addresses Loss of Plasticity in Continual Learning
by: Wang, Jiuqi, et al.
Published: (2025)
by: Wang, Jiuqi, et al.
Published: (2025)
Similar Items
-
Seemingly Redundant Modules Enhance Robust Odor Learning in Fruit Flies
by: Li, Haiyang, et al.
Published: (2025) -
A Low Latency Adaptive Coding Spiking Framework for Deep Reinforcement Learning
by: Qin, Lang, et al.
Published: (2022) -
Structure as Computation: Developmental Generation of Minimal Neural Circuits
by: Zhou, Duan
Published: (2026) -
Evolution Strategies at Scale: LLM Fine-Tuning Beyond Reinforcement Learning
by: Qiu, Xin, et al.
Published: (2025) -
SpikeRL: A Scalable and Energy-efficient Framework for Deep Spiking Reinforcement Learning
by: Tahmid, Tokey, et al.
Published: (2025)