Cover Image

Task Adaptation from Skills: Information Geometry, Disentanglement, and New Objectives for Unsupervised Reinforcement Learning

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Yang, Yucheng, Zhou, Tianyi, He, Qiang, Han, Lei, Pechenizkiy, Mykola, Fang, Meng
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Artificial Intelligence Information Theory I.2.6; I.2.8; G.3
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

PillagerBench: Benchmarking LLM-Based Agents in Competitive Minecraft Team Environments
by: Schipper, Olivier, et al.
Published: (2025)

AI and Machine Learning Approaches for Predicting Nanoparticles Toxicity The Critical Role of Physiochemical Properties
by: Yousaf, Iqra
Published: (2024)

A Parallel Hybrid Action Space Reinforcement Learning Model for Real-world Adaptive Traffic Signal Control
by: Wang, Yuxuan, et al.
Published: (2025)

TML-Bench: Benchmark for Data Science Agents on Tabular ML Tasks
by: Pinchuk, Mykola
Published: (2026)

Selective Progress-Aware Querying for Human-in-the-Loop Reinforcement Learning
by: Muraleedharan, Anujith, et al.
Published: (2025)

Sketch Decompositions for Classical Planning via Deep Reinforcement Learning
by: Aichmüller, Michael, et al.
Published: (2024)

Fractional Policy Gradients: Reinforcement Learning with Long-Term Memory
by: Pawar, Urvi, et al.
Published: (2025)

Zero-Shot Context Generalization in Reinforcement Learning from Few Training Contexts
by: Chapman, James, et al.
Published: (2025)

From Cumulative Constraints to Adaptive Runtime Safety Control for Nonstationary Reinforcement Learning
by: Tomashevskiy, Timofey
Published: (2026)

FlowRL: Flow-Augmented Few-Shot Reinforcement Learning for Semi-Structured Sensor Data
by: Pivezhandi, Mohammad, et al.
Published: (2024)

MOCHA: Multi-Objective Chebyshev Annealing for Agent Skill Optimization
by: Tanjim, Md Mehrab, et al.
Published: (2026)

From Theory to Practice with RAVEN-UCB: Addressing Non-Stationarity in Multi-Armed Bandits through Variance Adaptation
by: Fang, Junyi, et al.
Published: (2025)

GIRL: Generative Imagination Reinforcement Learning via Information-Theoretic Hallucination Control
by: Hiremath, Prakul Sunil
Published: (2026)

Predicting Future Actions of Reinforcement Learning Agents
by: Chung, Stephen, et al.
Published: (2024)

Evolving Programmatic Skill Networks
by: Shi, Haochen, et al.
Published: (2026)

Tackling Decision Processes with Non-Cumulative Objectives using Reinforcement Learning
by: Nägele, Maximilian, et al.
Published: (2024)

SMOSE: Sparse Mixture of Shallow Experts for Interpretable Reinforcement Learning in Continuous Control Tasks
by: Vincze, Mátyás, et al.
Published: (2024)

LeanProgress: Guiding Search for Neural Theorem Proving via Proof Progress Prediction
by: George, Robert Joseph, et al.
Published: (2025)

Predicting and improving test-time scaling laws via reward tail-guided search
by: Li, Muheng, et al.
Published: (2026)

NeSIG: A Neuro-Symbolic Method for Learning to Generate Planning Problems
by: Núñez-Molina, Carlos, et al.
Published: (2023)

Constrained Auto-Bidding via Generative Response Modeling
by: Yang, Eunseok, et al.
Published: (2026)

Learning to Select Goals in Automated Planning with Deep-Q Learning
by: Núñez-Molina, Carlos, et al.
Published: (2024)

Procedural Game Level Design with Deep Reinforcement Learning
by: Özkan, Miraç Buğra
Published: (2025)

An Aircraft Upset Recovery System with Reinforcement Learning
by: Demir, Mahir, et al.
Published: (2026)

Safe Reinforcement Learning with Preference-based Constraint Inference
by: Li, Chenglin, et al.
Published: (2026)

StepScorer: Accelerating Reinforcement Learning with Step-wise Scoring and Psychological Regret Modeling
by: Xu, Zhe
Published: (2026)

CORE: Towards Scalable and Efficient Causal Discovery with Reinforcement Learning
by: Sauter, Andreas W. M., et al.
Published: (2024)

Deep Reinforcement Learning for Day-to-day Dynamic Tolling in Tradable Credit Schemes
by: Wu, Xiaoyi, et al.
Published: (2025)

Umbrella Reinforcement Learning -- computationally efficient tool for hard non-linear problems
by: Nuzhin, Egor E., et al.
Published: (2024)

The Final-Stage Bottleneck: A Systematic Dissection of the R-Learner for Network Causal Inference
by: Sairam, S, et al.
Published: (2025)

From Next Token Prediction to (STRIPS) World Models
by: Núñez-Molina, Carlos, et al.
Published: (2025)

Hybrid-AIRL: Enhancing Inverse Reinforcement Learning with Supervised Expert Guidance
by: Silue, Bram, et al.
Published: (2025)

Joint Combinatorial Node Selection and Resource Allocations in the Lightning Network using Attention-based Reinforcement Learning
by: Salahshour, Mahdi, et al.
Published: (2024)

SCULPT: Constraint-Guided Pruned MCTS that Carves Efficient Paths for Mathematical Reasoning
by: Fang, Qitong, et al.
Published: (2026)

Sim-to-reality adaptation for Deep Reinforcement Learning applied to an underwater docking application
by: Chaarani, Alaaeddine, et al.
Published: (2026)

Learning Natural Language Constraints for Safe Reinforcement Learning of Language Agents
by: Chua, Jaymari, et al.
Published: (2025)

An Automatic Ground Collision Avoidance System with Reinforcement Learning
by: Sevgili, Seyyid Osman, et al.
Published: (2026)

PIRS: Physics-Informed Reward Shaping for SAC-Based Building Energy Management
by: Zaregarizi, Shadmehr, et al.
Published: (2026)

Are We Winning the Wrong Game? Revisiting Evaluation Practices for Long-Term Time Series Forecasting
by: Phungtua-eng, Thanapol, et al.
Published: (2026)

Building Minimal and Reusable Causal State Abstractions for Reinforcement Learning
by: Wang, Zizhao, et al.
Published: (2024)