Saved in:
| Main Author: | Chun, Zheng |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2501.03676 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Self-Supervised On-Policy Reinforcement Learning via Contrastive Proximal Policy Optimisation
by: Osman, Asim, et al.
Published: (2026)
by: Osman, Asim, et al.
Published: (2026)
Maximizing Rollout Informativeness under a Fixed Budget: A Submodular View of Tree Search for Tool-Use Agentic Reinforcement Learning
by: Hu, Yuelin, et al.
Published: (2026)
by: Hu, Yuelin, et al.
Published: (2026)
Autonomous AI Agents for Real-Time Affordable Housing Site Selection: Multi-Objective Reinforcement Learning Under Regulatory Constraints
by: Imanov, Olaf Yunus Laitinen, et al.
Published: (2026)
by: Imanov, Olaf Yunus Laitinen, et al.
Published: (2026)
Multi-level meta-reinforcement learning with skill-based curriculum
by: Yang, Sichen, et al.
Published: (2026)
by: Yang, Sichen, et al.
Published: (2026)
SafeRL-Lite: A Lightweight, Explainable, and Constrained Reinforcement Learning Library
by: Mishra, Satyam, et al.
Published: (2025)
by: Mishra, Satyam, et al.
Published: (2025)
A New Modeling to Feature Selection Based on the Fuzzy Rough Set Theory in Normal and Optimistic States on Hybrid Information Systems
by: Safarpour, Mohammad Hossein, et al.
Published: (2026)
by: Safarpour, Mohammad Hossein, et al.
Published: (2026)
GoldenStart: Q-Guided Priors and Entropy Control for Distilling Flow Policies
by: Zhang, He, et al.
Published: (2026)
by: Zhang, He, et al.
Published: (2026)
Active perception and disentangled representations allow continual, episodic zero and few-shot learning
by: Rawlinson, David, et al.
Published: (2026)
by: Rawlinson, David, et al.
Published: (2026)
Actor-Curator: Co-adaptive Curriculum Learning via Policy-Improvement Bandits for RL Post-Training
by: Gu, Zhengyao, et al.
Published: (2026)
by: Gu, Zhengyao, et al.
Published: (2026)
Foundation Models as World Models: A Foundational Study in Text-Based GridWorlds
by: Sasso, Remo, et al.
Published: (2025)
by: Sasso, Remo, et al.
Published: (2025)
RoboMoRe: LLM-based Robot Co-design via Joint Optimization of Morphology and Reward
by: Fang, Jiawei, et al.
Published: (2025)
by: Fang, Jiawei, et al.
Published: (2025)
Exploration with Foundation Models: Capabilities, Limitations, and Hybrid Approaches
by: Sasso, Remo, et al.
Published: (2025)
by: Sasso, Remo, et al.
Published: (2025)
Strategizing Equitable Transit Evacuations: A Data-Driven Reinforcement Learning Approach
by: Tang, Fang, et al.
Published: (2024)
by: Tang, Fang, et al.
Published: (2024)
Communicating Plans, Not Percepts: Scalable Multi-Agent Coordination with Embodied World Models
by: Hill, Brennen A., et al.
Published: (2025)
by: Hill, Brennen A., et al.
Published: (2025)
A Comparison Between Decision Transformers and Traditional Offline Reinforcement Learning Algorithms
by: Caunhye, Ali Murtaza, et al.
Published: (2025)
by: Caunhye, Ali Murtaza, et al.
Published: (2025)
Bayesian Conservative Policy Optimization (BCPO): A Novel Uncertainty-Calibrated Offline Reinforcement Learning with Credible Lower Bounds
by: Chatterjee, Debashis
Published: (2026)
by: Chatterjee, Debashis
Published: (2026)
SMOSE: Sparse Mixture of Shallow Experts for Interpretable Reinforcement Learning in Continuous Control Tasks
by: Vincze, Mátyás, et al.
Published: (2024)
by: Vincze, Mátyás, et al.
Published: (2024)
Robustness of Reinforcement Learning-Based Traffic Signal Control under Incidents: A Comparative Study
by: Nguyen, Dang Viet Anh, et al.
Published: (2025)
by: Nguyen, Dang Viet Anh, et al.
Published: (2025)
A Survey of Reinforcement Learning for Optimization in Automation
by: Farooq, Ahmad, et al.
Published: (2025)
by: Farooq, Ahmad, et al.
Published: (2025)
Active Causal Experimentalist (ACE): Learning Intervention Strategies via Direct Preference Optimization
by: Cooper, Patrick, et al.
Published: (2026)
by: Cooper, Patrick, et al.
Published: (2026)
From Imitation to Interaction: Mastering Game of Schnapsen with Shallow Reinforcement Learning
by: Klačan, Ján, et al.
Published: (2026)
by: Klačan, Ján, et al.
Published: (2026)
Amazon Locker Capacity Management
by: Sethuraman, Samyukta, et al.
Published: (2023)
by: Sethuraman, Samyukta, et al.
Published: (2023)
The Mirror Loop: Recursive Non-Convergence in Generative Reasoning Systems
by: DeVilling, Bentley
Published: (2025)
by: DeVilling, Bentley
Published: (2025)
Streaming Continual Learning for Unified Adaptive Intelligence in Dynamic Environments
by: Giannini, Federico, et al.
Published: (2026)
by: Giannini, Federico, et al.
Published: (2026)
Generative World Models of Tasks: LLM-Driven Hierarchical Scaffolding for Embodied Agents
by: Hill, Brennen
Published: (2025)
by: Hill, Brennen
Published: (2025)
Maximum Entropy Relaxation of Multi-Way Cardinality Constraints for Synthetic Population Generation
by: Pachet, François, et al.
Published: (2026)
by: Pachet, François, et al.
Published: (2026)
Enhancing Diversity in Multi-objective Feature Selection
by: Miyandoab, Sevil Zanjani, et al.
Published: (2024)
by: Miyandoab, Sevil Zanjani, et al.
Published: (2024)
Statistical Guarantees for Lifelong Reinforcement Learning using PAC-Bayes Theory
by: Zhang, Zhi, et al.
Published: (2024)
by: Zhang, Zhi, et al.
Published: (2024)
An Improved Adaptive PID Optimizer with Enhanced Convergence and Stability for Deep Learning
by: Saini, Saurabh, et al.
Published: (2026)
by: Saini, Saurabh, et al.
Published: (2026)
Prediction-Based Markov Violation Scores for Detecting Non-Markovian Observations in Reinforcement Learning
by: Mysore, Naveen
Published: (2026)
by: Mysore, Naveen
Published: (2026)
Necessary and Sufficient Conditions for Optimal Decision Trees using Dynamic Programming
by: van der Linden, Jacobus G. M., et al.
Published: (2023)
by: van der Linden, Jacobus G. M., et al.
Published: (2023)
Evolving machine learning workflows through interactive AutoML
by: Barbudo, Rafael, et al.
Published: (2024)
by: Barbudo, Rafael, et al.
Published: (2024)
Machine Learning Algorithms for Improving Black Box Optimization Solvers
by: Kimiaei, Morteza, et al.
Published: (2025)
by: Kimiaei, Morteza, et al.
Published: (2025)
A Structural Threshold in Decision Capacity Governs Collapse in Self-Play Reinforcement Learning
by: Kujur, Arahan
Published: (2026)
by: Kujur, Arahan
Published: (2026)
EvoPref: Multi-Objective Evolutionary Optimization Discovers Diverse LLM Alignments Beyond Gradient Descent
by: Guo, Dongxin, et al.
Published: (2026)
by: Guo, Dongxin, et al.
Published: (2026)
STACHE: Local Black-Box Explanations for Reinforcement Learning Policies
by: Elashkin, Andrew, et al.
Published: (2025)
by: Elashkin, Andrew, et al.
Published: (2025)
LeLaR: The First In-Orbit Demonstration of an AI-Based Satellite Attitude Controller
by: Djebko, Kirill, et al.
Published: (2025)
by: Djebko, Kirill, et al.
Published: (2025)
Optimizing Donor Outreach for Blood Collection Sessions: A Scalable Decision Support Framework
by: Carneiro, André, et al.
Published: (2026)
by: Carneiro, André, et al.
Published: (2026)
Can a Bayesian Oracle Prevent Harm from an Agent?
by: Bengio, Yoshua, et al.
Published: (2024)
by: Bengio, Yoshua, et al.
Published: (2024)
Diffusion-MPC in Discrete Domains: Feasibility Constraints, Horizon Effects, and Critic Alignment: Case study with Tetris
by: Wang, Haochuan Kevin
Published: (2026)
by: Wang, Haochuan Kevin
Published: (2026)
Similar Items
-
Self-Supervised On-Policy Reinforcement Learning via Contrastive Proximal Policy Optimisation
by: Osman, Asim, et al.
Published: (2026) -
Maximizing Rollout Informativeness under a Fixed Budget: A Submodular View of Tree Search for Tool-Use Agentic Reinforcement Learning
by: Hu, Yuelin, et al.
Published: (2026) -
Autonomous AI Agents for Real-Time Affordable Housing Site Selection: Multi-Objective Reinforcement Learning Under Regulatory Constraints
by: Imanov, Olaf Yunus Laitinen, et al.
Published: (2026) -
Multi-level meta-reinforcement learning with skill-based curriculum
by: Yang, Sichen, et al.
Published: (2026) -
SafeRL-Lite: A Lightweight, Explainable, and Constrained Reinforcement Learning Library
by: Mishra, Satyam, et al.
Published: (2025)