Cover Image

Reinforcement Learning for Reachability: Guaranteeing Asymptotic Optimality

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Palasamudram, Amogh, Svoboda, Jakub, Bansal, Suguman, Chatterjee, Krishnendu
Format:	Preprint
Published:	2026
Subjects:	Machine Learning Computer Science and Game Theory 68Q32 I.2.6
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Adaptive Discretization in Online Reinforcement Learning
by: Sinclair, Sean R., et al.
Published: (2021)

Near-Optimal Consistency-Robustness Trade-Offs for Learning-Augmented Online Knapsack Problems
by: Daneshvaramoli, Mohammadreza, et al.
Published: (2024)

Agnostic Learning under Targeted Poisoning: Optimal Rates and the Role of Randomness
by: Chornomaz, Bogdan, et al.
Published: (2025)

Ambiguous Online Learning
by: Kosoy, Vanessa
Published: (2025)

Adversarial Learning in Games with Bandit Feedback: Logarithmic Pure-Strategy Maximin Regret
by: Ito, Shinji, et al.
Published: (2026)

Reinforcement Learning in MDPs with Information-Ordered Policies
by: Zhang, Zhongjun, et al.
Published: (2025)

Aligning Inductive Bias for Data-Efficient Generalization in State Space Models
by: Chen, Qiyu, et al.
Published: (2025)

Regret Bounds for Robust Online Decision Making
by: Appel, Alexander, et al.
Published: (2025)

Statistical Guarantees for Lifelong Reinforcement Learning using PAC-Bayes Theory
by: Zhang, Zhi, et al.
Published: (2024)

Frequency Principle: Fourier Analysis Sheds Light on Deep Neural Networks
by: Xu, Zhi-Qin John, et al.
Published: (2019)

Backpropagation Through Time For Networks With Long-Term Dependencies
by: Bird, George, et al.
Published: (2021)

The Current and Future Perspectives of Zinc Oxide Nanoparticles in the Treatment of Diabetes Mellitus
by: Yousaf, Iqra
Published: (2024)

Margin in Abstract Spaces
by: Ashlagi, Yair, et al.
Published: (2026)

Sparse Knowledge Distillation: A Mathematical Framework for Probability-Domain Temperature Scaling and Multi-Stage Compression
by: Flouro, Aaron R., et al.
Published: (2026)

Golden Handcuffs make safer AI agents
by: Ebtekar, Aram, et al.
Published: (2026)

Retrieval-Augmented Memory for Online Learning
by: Du, Wenzhang
Published: (2025)

Mitigating Catastrophic Forgetting in Streaming Generative and Predictive Learning via Stateful Replay
by: Du, Wenzhang
Published: (2025)

Superior Scoring Rules for Probabilistic Evaluation of Single-Label Multi-Class Classification Tasks
by: Ahmadian, Rouhollah, et al.
Published: (2024)

Instance-Dependent Regret Bounds for Learning Two-Player Zero-Sum Games with Bandit Feedback
by: Ito, Shinji, et al.
Published: (2025)

Tricks and Plug-ins for Gradient Boosting with Transformers
by: Fang, Biyi, et al.
Published: (2025)

Diagnosing Multi-step Reasoning Failures in Black-box LLMs via Stepwise Confidence Attribution
by: Liu, Xiaoou, et al.
Published: (2026)

MMD-Balls as Credal Sets: A PAC-Bayesian Framework for Epistemic Uncertainty in Test-Time Adaptation
by: Ariq, Ahanaf Hasan
Published: (2026)

Inductive Venn-Abers and related regressors
by: Petej, Ivan, et al.
Published: (2026)

Aggregation in conformal e-classification
by: Vovk, Vladimir
Published: (2026)

Theoretical Analysis of Positional Encodings in Transformer Models: Impact on Expressiveness and Generalization
by: Li, Yin
Published: (2025)

Optimistic Feasible Search for Closed-Loop Fair Threshold Decision-Making
by: Du, Wenzhang
Published: (2025)

Binarized Neural Networks Converge Toward Algorithmic Simplicity: Empirical Support for the Learning-as-Compression Hypothesis
by: Sakabe, Eduardo Y., et al.
Published: (2025)

Incentives in Federated Learning with Heterogeneous Agents
by: Procaccia, Ariel D., et al.
Published: (2025)

Position: Uncertainty Quantification in LLMs is Just Unsupervised Clustering
by: Chen, Tiejin, et al.
Published: (2026)

Energy-Efficient Information Representation in MNIST Classification Using Biologically Inspired Learning
by: Stricker, Patrick, et al.
Published: (2026)

A Reduction from Delayed to Immediate Feedback for Online Convex Optimization with Improved Guarantees
by: Ryabchenko, Alexander, et al.
Published: (2026)

AI Agents for the Dhumbal Card Game: A Comparative Study
by: Malla, Sahaj Raj
Published: (2025)

Understanding the Nature of Generative AI as Threshold Logic in High-Dimensional Space
by: Levin, Ilya
Published: (2026)

Graded Transformers
by: Shaska Sr, Tony
Published: (2025)

DualGFL: Federated Learning with a Dual-Level Coalition-Auction Game
by: Chen, Xiaobing, et al.
Published: (2024)

ZetA: A Riemann Zeta-Scaled Extension of Adam for Deep Learning
by: BC, Samiksha
Published: (2025)

Advances in Set Function Learning: A Survey of Techniques and Applications
by: Xie, Jiahao, et al.
Published: (2025)

SuS: Strategy-aware Surprise for Intrinsic Exploration
by: Kashirskiy, Mark, et al.
Published: (2026)

The two clocks and the innovation window: When and how generative models learn rules
by: Wang, Binxu, et al.
Published: (2026)

Uniform Computability of PAC Learning
by: Brattka, Vasco, et al.
Published: (2026)