Information-Theoretic Policy Pre-Training with Empowerment
Fuente:
arXiv
Saved in:
| Main Authors: | Schneider, Moritz, Krug, Robert, Vaskevicius, Narunas, Palmieri, Luigi, Volpp, Michael, Boedecker, Joschka |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
The Surprising Ineffectiveness of Pre-Trained Visual Representations for Model-Based Reinforcement Learning
by: Schneider, Moritz, et al.
Published: (2024)
by: Schneider, Moritz, et al.
Published: (2024)
MSG: Multi-Stream Generative Policies for Sample-Efficient Robotic Manipulation
by: von Hartz, Jan Ole, et al.
Published: (2025)
by: von Hartz, Jan Ole, et al.
Published: (2025)
The Unreasonable Effectiveness of Discrete-Time Gaussian Process Mixtures for Robot Policy Learning
by: von Hartz, Jan Ole, et al.
Published: (2025)
by: von Hartz, Jan Ole, et al.
Published: (2025)
Learning What Matters: Adaptive Information-Theoretic Objectives for Robot Exploration
by: Yu, Youwei, et al.
Published: (2026)
by: Yu, Youwei, et al.
Published: (2026)
Spectral Alignment in Forward-Backward Representations via Temporal Abstraction
by: Azad, Seyed Mahdi B., et al.
Published: (2026)
by: Azad, Seyed Mahdi B., et al.
Published: (2026)
A Provable Approach for End-to-End Safe Reinforcement Learning
by: Wachi, Akifumi, et al.
Published: (2025)
by: Wachi, Akifumi, et al.
Published: (2025)
SPRINT: Scalable Policy Pre-Training via Language Instruction Relabeling
by: Zhang, Jesse, et al.
Published: (2023)
by: Zhang, Jesse, et al.
Published: (2023)
An Effective Information Theoretic Framework for Channel Pruning
by: Chen, Yihao, et al.
Published: (2024)
by: Chen, Yihao, et al.
Published: (2024)
An Information-Theoretic Criterion for Efficient Data Synthesis
by: Li, Hanyu, et al.
Published: (2026)
by: Li, Hanyu, et al.
Published: (2026)
Machine Unlearning via Information Theoretic Regularization
by: Xu, Shizhou, et al.
Published: (2025)
by: Xu, Shizhou, et al.
Published: (2025)
Revisiting Safe Exploration in Safe Reinforcement learning
by: Eckel, David, et al.
Published: (2024)
by: Eckel, David, et al.
Published: (2024)
Fairness Overfitting in Machine Learning: An Information-Theoretic Perspective
by: Laakom, Firas, et al.
Published: (2025)
by: Laakom, Firas, et al.
Published: (2025)
Information-Theoretic State Variable Selection for Reinforcement Learning
by: Westphal, Charles, et al.
Published: (2024)
by: Westphal, Charles, et al.
Published: (2024)
Information-Theoretic Equivalence of Entropic Multi-Marginal Optimal Transport: A Theory for Multi-Agent Communication
by: Wang, Shuchan
Published: (2022)
by: Wang, Shuchan
Published: (2022)
Uncertainty Quantification and Data Efficiency in AI: An Information-Theoretic Perspective
by: Simeone, Osvaldo, et al.
Published: (2025)
by: Simeone, Osvaldo, et al.
Published: (2025)
GraphEQA: Using 3D Semantic Scene Graphs for Real-time Embodied Question Answering
by: Saxena, Saumya, et al.
Published: (2024)
by: Saxena, Saumya, et al.
Published: (2024)
The Causal Description Gap: Information-Theoretic Separations Across Pearl's Hierarchy
by: Emadi, Seyed Morteza
Published: (2026)
by: Emadi, Seyed Morteza
Published: (2026)
Context Channel Capacity: An Information-Theoretic Framework for Understanding Catastrophic Forgetting
by: Cheng, Ran
Published: (2026)
by: Cheng, Ran
Published: (2026)
Rethinking KV Cache Eviction via a Unified Information-Theoretic Objective
by: Yang, Jiaming, et al.
Published: (2026)
by: Yang, Jiaming, et al.
Published: (2026)
Probing the Information Theoretical Roots of Spatial Dependence Measures
by: Wang, Zhangyu, et al.
Published: (2024)
by: Wang, Zhangyu, et al.
Published: (2024)
General Information Metrics for Improving AI Model Training Efficiency
by: Xu, Jianfeng, et al.
Published: (2025)
by: Xu, Jianfeng, et al.
Published: (2025)
Neural Networks Learn Generic Multi-Index Models Near Information-Theoretic Limit
by: Zhang, Bohan, et al.
Published: (2025)
by: Zhang, Bohan, et al.
Published: (2025)
Flexible Variational Information Bottleneck: Achieving Diverse Compression with a Single Training
by: Kudo, Sota, et al.
Published: (2024)
by: Kudo, Sota, et al.
Published: (2024)
An Information Theoretic Perspective on Agentic System Design
by: He, Shizhe, et al.
Published: (2025)
by: He, Shizhe, et al.
Published: (2025)
Latent Policy Steering with Embodiment-Agnostic Pretrained World Models
by: Wang, Yiqi, et al.
Published: (2025)
by: Wang, Yiqi, et al.
Published: (2025)
Latent-Predictive Empowerment: Measuring Empowerment without a Simulator
by: Levy, Andrew, et al.
Published: (2024)
by: Levy, Andrew, et al.
Published: (2024)
Efficient Online RL Fine Tuning with Offline Pre-trained Policy Only
by: Xiao, Wei, et al.
Published: (2025)
by: Xiao, Wei, et al.
Published: (2025)
A General Error-Theoretical Analysis Framework for Constructing Compression Strategies
by: Zhang, Boyang, et al.
Published: (2025)
by: Zhang, Boyang, et al.
Published: (2025)
The Agent Capability Problem: Predicting Solvability Through Information-Theoretic Bounds
by: Lutati, Shahar
Published: (2025)
by: Lutati, Shahar
Published: (2025)
Unsupervised Learning of Efficient Exploration: Pre-training Adaptive Policies via Self-Imposed Goals
by: Pappalardo, Octavio
Published: (2026)
by: Pappalardo, Octavio
Published: (2026)
Multimodal Visual-Tactile Representation Learning through Self-Supervised Contrastive Pre-Training
by: Dave, Vedant, et al.
Published: (2024)
by: Dave, Vedant, et al.
Published: (2024)
Vintix II: Decision Pre-Trained Transformer is a Scalable In-Context Reinforcement Learner
by: Polubarov, Andrei, et al.
Published: (2026)
by: Polubarov, Andrei, et al.
Published: (2026)
Off-Policy Actor-Critic for Adversarial Observation Robustness: Virtual Alternative Training via Symmetric Policy Evaluation
by: Nakanishi, Kosuke, et al.
Published: (2025)
by: Nakanishi, Kosuke, et al.
Published: (2025)
Compression via Pre-trained Transformers: A Study on Byte-Level Multimodal Data
by: Heurtel-Depeiges, David, et al.
Published: (2024)
by: Heurtel-Depeiges, David, et al.
Published: (2024)
SR-Reward: Taking The Path More Traveled
by: Azad, Seyed Mahdi B., et al.
Published: (2025)
by: Azad, Seyed Mahdi B., et al.
Published: (2025)
Context-Conditional Navigation with a Learning-Based Terrain- and Robot-Aware Dynamics Model
by: Guttikonda, Suresh, et al.
Published: (2023)
by: Guttikonda, Suresh, et al.
Published: (2023)
Latent Linear Quadratic Regulator for Robotic Control Tasks
by: Zhang, Yuan, et al.
Published: (2024)
by: Zhang, Yuan, et al.
Published: (2024)
The Art of Imitation: Learning Long-Horizon Manipulation Tasks from Few Demonstrations
by: von Hartz, Jan Ole, et al.
Published: (2024)
by: von Hartz, Jan Ole, et al.
Published: (2024)
A Mechanistic Analysis of Sim-and-Real Co-Training in Generative Robot Policies
by: Lei, Yu, et al.
Published: (2026)
by: Lei, Yu, et al.
Published: (2026)
Informational Embodiment: Computational role of information structure in codes and robots
by: Pitti, Alexandre, et al.
Published: (2024)
by: Pitti, Alexandre, et al.
Published: (2024)
Similar Items
-
The Surprising Ineffectiveness of Pre-Trained Visual Representations for Model-Based Reinforcement Learning
by: Schneider, Moritz, et al.
Published: (2024) -
MSG: Multi-Stream Generative Policies for Sample-Efficient Robotic Manipulation
by: von Hartz, Jan Ole, et al.
Published: (2025) -
The Unreasonable Effectiveness of Discrete-Time Gaussian Process Mixtures for Robot Policy Learning
by: von Hartz, Jan Ole, et al.
Published: (2025) -
Learning What Matters: Adaptive Information-Theoretic Objectives for Robot Exploration
by: Yu, Youwei, et al.
Published: (2026) -
Spectral Alignment in Forward-Backward Representations via Temporal Abstraction
by: Azad, Seyed Mahdi B., et al.
Published: (2026)