Cover Image

Confidence Aware Inverse Constrained Reinforcement Learning

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Subramanian, Sriram Ganapathi, Liu, Guiliang, Elmahgiubi, Mohammed, Rezaee, Kasra, Poupart, Pascal
Format:	Preprint
Published:	2024
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

A Comprehensive Survey on Inverse Constrained Reinforcement Learning: Definitions, Progress and Challenges
by: Liu, Guiliang, et al.
Published: (2024)

Learning to Negotiate via Voluntary Commitment
by: Zhu, Shuhui, et al.
Published: (2025)

Learning Soft Driving Constraints from Vectorized Scene Embeddings while Imitating Expert Trajectories
by: Mobarakeh, Niloufar Saeidi, et al.
Published: (2024)

Vectorized Representation Dreamer (VRD): Dreaming-Assisted Multi-Agent Motion-Forecasting
by: Schofield, Hunter, et al.
Published: (2024)

How Useful is Intermittent, Asynchronous Expert Feedback for Bayesian Optimization?
by: Kristiadi, Agustinus, et al.
Published: (2024)

Provably Efficient Exploration in Inverse Constrained Reinforcement Learning
by: Yue, Bo, et al.
Published: (2024)

CAPS: Context-Aware Priority Sampling for Enhanced Imitation Learning in Autonomous Driving
by: Mirkhani, Hamidreza, et al.
Published: (2025)

Offline Inverse Constrained Reinforcement Learning for Safe-Critical Decision Making in Healthcare
by: Fang, Nan, et al.
Published: (2024)

Validity Learning on Failures: Mitigating the Distribution Shift in Autonomous Vehicle Planning
by: Arasteh, Fazel, et al.
Published: (2024)

Why Online Reinforcement Learning is Causal
by: Schulte, Oliver, et al.
Published: (2024)

Beyond Simulation: Benchmarking World Models for Planning and Causality in Autonomous Driving
by: Schofield, Hunter, et al.
Published: (2025)

Simplifying Bayesian Optimization Via In-Context Direct Optimum Sampling
by: de Carvalho, Gustavo Sutter Pessurno, et al.
Published: (2025)

Preventing Arbitrarily High Confidence on Far-Away Data in Point-Estimated Discriminative Neural Networks
by: Rashid, Ahmad, et al.
Published: (2023)

Augmenting Safety-Critical Driving Scenarios while Preserving Similarity to Expert Trajectories
by: Mirkhani, Hamidreza, et al.
Published: (2024)

Vulnerability Analysis of Safe Reinforcement Learning via Inverse Constrained Reinforcement Learning
by: Fan, Jialiang, et al.
Published: (2026)

Basis Transformers for Multi-Task Tabular Regression
by: Loh, Wei Min, et al.
Published: (2025)

LACONIC: Length-Aware Constrained Reinforcement Learning for LLM
by: Liu, Chang, et al.
Published: (2026)

Calibrated One Round Federated Learning with Bayesian Inference in the Predictive Space
by: Hasan, Mohsin, et al.
Published: (2023)

Q-Learning with Shift-Aware Upper Confidence Bound in Non-Stationary Reinforcement Learning
by: Bui, Ha Manh, et al.
Published: (2025)

FedLog: Personalized Federated Classification with Less Communication and More Flexibility
by: Yu, Haolin, et al.
Published: (2024)

TDHook: A Lightweight Framework for Interpretability
by: Poupart, Yoann
Published: (2025)

Subject-driven Text-to-Image Generation via Preference-based Reinforcement Learning
by: Miao, Yanting, et al.
Published: (2024)

Confidence-Aware Deep Learning for Load Plan Adjustments in the Parcel Service Industry
by: Bruys, Thomas, et al.
Published: (2024)

ConstrainedSQL: Training LLMs for Text2SQL via Constrained Reinforcement Learning
by: Chen, Weiqin, et al.
Published: (2025)

Measures of Variability for Risk-averse Policy Gradient
by: Luo, Yudong, et al.
Published: (2025)

Time Is Effort: Estimating Human Post-Editing Time for Grammar Error Correction Tool Evaluation
by: Vadehra, Ankit, et al.
Published: (2025)

A Practical Algorithm for Feature-Rich, Non-Stationary Bandit Problems
by: Loh, Wei Min, et al.
Published: (2026)

Fast Algorithm for Constrained Linear Inverse Problems
by: Sheriff, Mohammed Rayyan, et al.
Published: (2022)

Inverse Reinforcement Learning without Reinforcement Learning
by: Swamy, Gokul, et al.
Published: (2023)

A Critical Look At Tokenwise Reward-Guided Text Generation
by: Rashid, Ahmad, et al.
Published: (2024)

A Simple Mixture Policy Parameterization for Improving Sample Efficiency of CVaR Optimization
by: Luo, Yudong, et al.
Published: (2024)

Reflect-then-Plan: Offline Model-Based Planning through a Doubly Bayesian Lens
by: Jeong, Jihwan, et al.
Published: (2025)

Distributional Inverse Reinforcement Learning
by: Wu, Feiyang, et al.
Published: (2025)

Hierarchical Upper Confidence Bounds for Constrained Online Learning
by: Baheri, Ali
Published: (2024)

Adversarial Inverse Reinforcement Learning for Mean Field Games
by: Chen, Yang, et al.
Published: (2021)

Uncertainty-Aware Post-Hoc Calibration: Mitigating Confidently Incorrect Predictions Beyond Calibration Metrics
by: Gharoun, Hassan, et al.
Published: (2025)

Knowledge Distillation for Efficient Transformer-Based Reinforcement Learning in Hardware-Constrained Energy Management Systems
by: Henrich, Pascal, et al.
Published: (2026)

Towards Generalized Inverse Reinforcement Learning
by: Dong, Chaosheng, et al.
Published: (2024)

The Virtues of Pessimism in Inverse Reinforcement Learning
by: Wu, David, et al.
Published: (2024)

PAC Apprenticeship Learning with Bayesian Active Inverse Reinforcement Learning
by: Bajgar, Ondrej, et al.
Published: (2025)