Mutual Information Tracks Policy Coherence in Reinforcement Learning
Fuente:
arXiv
Saved in:
| Main Authors: | Reid, Cameron, Hafez, Wael, Nazeri, Amirhossein |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
The Informational Cost of Agency: A Bounded Measure of Interaction Efficiency for Deployed Reinforcement Learning
by: Hafez, Wael, et al.
Published: (2026)
by: Hafez, Wael, et al.
Published: (2026)
Information-Theoretic Framework for Self-Adapting Model Predictive Controllers
by: Hafez, Wael, et al.
Published: (2026)
by: Hafez, Wael, et al.
Published: (2026)
Entropy-Based Non-Invasive Reliability Monitoring of Convolutional Neural Networks
by: Nazeri, Amirhossein, et al.
Published: (2025)
by: Nazeri, Amirhossein, et al.
Published: (2025)
Skill-aware Mutual Information Optimisation for Generalisation in Reinforcement Learning
by: Yu, Xuehui, et al.
Published: (2024)
by: Yu, Xuehui, et al.
Published: (2024)
V-Max: A Reinforcement Learning Framework for Autonomous Driving
by: Charraut, Valentin, et al.
Published: (2025)
by: Charraut, Valentin, et al.
Published: (2025)
Discrete Variational Autoencoding via Policy Search
by: Drolet, Michael, et al.
Published: (2025)
by: Drolet, Michael, et al.
Published: (2025)
Token Statistics Reveal Conversational Drift in Multi-turn LLM Interaction
by: Hafez, Wael, et al.
Published: (2026)
by: Hafez, Wael, et al.
Published: (2026)
Rethinking Policy Diversity in Ensemble Policy Gradient in Large-Scale Reinforcement Learning
by: Shitanda, Naoki, et al.
Published: (2026)
by: Shitanda, Naoki, et al.
Published: (2026)
ReinforceGen: Hybrid Skill Policies with Automated Data Generation and Reinforcement Learning
by: Zhou, Zihan, et al.
Published: (2025)
by: Zhou, Zihan, et al.
Published: (2025)
A Mathematical Theory of Agency and Intelligence
by: Hafez, Wael, et al.
Published: (2026)
by: Hafez, Wael, et al.
Published: (2026)
Diffusion Policies with Value-Conditional Optimization for Offline Reinforcement Learning
by: Ma, Yunchang, et al.
Published: (2025)
by: Ma, Yunchang, et al.
Published: (2025)
Adaptive Advantage-Guided Policy Regularization for Offline Reinforcement Learning
by: Liu, Tenglong, et al.
Published: (2024)
by: Liu, Tenglong, et al.
Published: (2024)
RLDG: Robotic Generalist Policy Distillation via Reinforcement Learning
by: Xu, Charles, et al.
Published: (2024)
by: Xu, Charles, et al.
Published: (2024)
Dual Action Policy for Robust Sim-to-Real Reinforcement Learning
by: Terence, Ng Wen Zheng, et al.
Published: (2024)
by: Terence, Ng Wen Zheng, et al.
Published: (2024)
Uncertainty-Based Smooth Policy Regularisation for Reinforcement Learning with Few Demonstrations
by: Zhu, Yujie, et al.
Published: (2025)
by: Zhu, Yujie, et al.
Published: (2025)
FlowQ: Energy-Guided Flow Policies for Offline Reinforcement Learning
by: Alles, Marvin, et al.
Published: (2025)
by: Alles, Marvin, et al.
Published: (2025)
Robot Policy Transfer with Online Demonstrations: An Active Reinforcement Learning Approach
by: Hou, Muhan, et al.
Published: (2025)
by: Hou, Muhan, et al.
Published: (2025)
Exploiting Hybrid Policy in Reinforcement Learning for Interpretable Temporal Logic Manipulation
by: Zhang, Hao, et al.
Published: (2024)
by: Zhang, Hao, et al.
Published: (2024)
Towards Robust Policy: Enhancing Offline Reinforcement Learning with Adversarial Attacks and Defenses
by: Nguyen, Thanh, et al.
Published: (2024)
by: Nguyen, Thanh, et al.
Published: (2024)
Enhancing Hardware Fault Tolerance in Machines with Reinforcement Learning Policy Gradient Algorithms
by: Schoepp, Sheila, et al.
Published: (2024)
by: Schoepp, Sheila, et al.
Published: (2024)
Continual Policy Distillation of Reinforcement Learning-based Controllers for Soft Robotic In-Hand Manipulation
by: Li, Lanpei, et al.
Published: (2024)
by: Li, Lanpei, et al.
Published: (2024)
Trust Region Inverse Reinforcement Learning: Explicit Dual Ascent using Local Policy Updates
by: Diwan, Anish, et al.
Published: (2026)
by: Diwan, Anish, et al.
Published: (2026)
REFINE-DP: Diffusion Policy Fine-tuning for Humanoid Loco-manipulation via Reinforcement Learning
by: Gu, Zhaoyuan, et al.
Published: (2026)
by: Gu, Zhaoyuan, et al.
Published: (2026)
Distilling Reinforcement Learning Policies for Interpretable Robot Locomotion: Gradient Boosting Machines and Symbolic Regression
by: Acero, Fernando, et al.
Published: (2024)
by: Acero, Fernando, et al.
Published: (2024)
Multi-Agent Reinforcement Learning for Unmanned Aerial Vehicle Coordination by Multi-Critic Policy Gradient Optimization
by: Alon, Yoav, et al.
Published: (2020)
by: Alon, Yoav, et al.
Published: (2020)
Bootstrapping Reinforcement Learning with Sub-optimal Policies for Autonomous Driving
by: Zhang, Zhihao, et al.
Published: (2025)
by: Zhang, Zhihao, et al.
Published: (2025)
Curriculum Is More Influential Than Haptic Information During Reinforcement Learning of Object Manipulation Against Gravity
by: Ojaghi, Pegah, et al.
Published: (2024)
by: Ojaghi, Pegah, et al.
Published: (2024)
Reinforcement Learning with Action Chunking
by: Li, Qiyang, et al.
Published: (2025)
by: Li, Qiyang, et al.
Published: (2025)
RILe: Reinforced Imitation Learning
by: Albaba, Mert, et al.
Published: (2024)
by: Albaba, Mert, et al.
Published: (2024)
Rating-based Reinforcement Learning
by: White, Devin, et al.
Published: (2023)
by: White, Devin, et al.
Published: (2023)
Imagination Policy: Using Generative Point Cloud Models for Learning Manipulation Policies
by: Huang, Haojie, et al.
Published: (2024)
by: Huang, Haojie, et al.
Published: (2024)
Safety Optimized Reinforcement Learning via Multi-Objective Policy Optimization
by: Honari, Homayoun, et al.
Published: (2024)
by: Honari, Homayoun, et al.
Published: (2024)
Automating the Refinement of Reinforcement Learning Specifications
by: Ambadkar, Tanmay, et al.
Published: (2025)
by: Ambadkar, Tanmay, et al.
Published: (2025)
Privileged Sensing Scaffolds Reinforcement Learning
by: Hu, Edward S., et al.
Published: (2024)
by: Hu, Edward S., et al.
Published: (2024)
Sampling-Based Safe Reinforcement Learning
by: Vignola, Luca, et al.
Published: (2026)
by: Vignola, Luca, et al.
Published: (2026)
Reactive Diffusion Policy: Slow-Fast Visual-Tactile Policy Learning for Contact-Rich Manipulation
by: Xue, Han, et al.
Published: (2025)
by: Xue, Han, et al.
Published: (2025)
Causal Flow Q-Learning for Robust Offline Reinforcement Learning
by: Li, Mingxuan, et al.
Published: (2026)
by: Li, Mingxuan, et al.
Published: (2026)
Offline Goal-Conditioned Reinforcement Learning for Safety-Critical Tasks with Recovery Policy
by: Cao, Chenyang, et al.
Published: (2024)
by: Cao, Chenyang, et al.
Published: (2024)
IMLE Policy: Fast and Sample Efficient Visuomotor Policy Learning via Implicit Maximum Likelihood Estimation
by: Rana, Krishan, et al.
Published: (2025)
by: Rana, Krishan, et al.
Published: (2025)
Handling Delay in Real-Time Reinforcement Learning
by: Anokhin, Ivan, et al.
Published: (2025)
by: Anokhin, Ivan, et al.
Published: (2025)
Similar Items
-
The Informational Cost of Agency: A Bounded Measure of Interaction Efficiency for Deployed Reinforcement Learning
by: Hafez, Wael, et al.
Published: (2026) -
Information-Theoretic Framework for Self-Adapting Model Predictive Controllers
by: Hafez, Wael, et al.
Published: (2026) -
Entropy-Based Non-Invasive Reliability Monitoring of Convolutional Neural Networks
by: Nazeri, Amirhossein, et al.
Published: (2025) -
Skill-aware Mutual Information Optimisation for Generalisation in Reinforcement Learning
by: Yu, Xuehui, et al.
Published: (2024) -
V-Max: A Reinforcement Learning Framework for Autonomous Driving
by: Charraut, Valentin, et al.
Published: (2025)