Cover Image

How Log-Barrier Helps Exploration in Policy Optimization

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Cesani, Leonardo, Papini, Matteo, Restelli, Marcello
Format:	Preprint
Published:	2026
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Statistical Analysis of Policy Space Compression Problem
by: Molaei, Majid, et al.
Published: (2024)

Projection by Convolution: Optimal Sample Complexity for Reinforcement Learning in Continuous-Space MDPs
by: Maran, Davide, et al.
Published: (2024)

From Parameters to Behaviors: Unsupervised Compression of the Policy Space
by: Tenedini, Davide, et al.
Published: (2025)

How to Explore with Belief: State Entropy Maximization in POMDPs
by: Zamboni, Riccardo, et al.
Published: (2024)

Safe Exploration Using Bayesian World Models and Log-Barrier Optimization
by: As, Yarden, et al.
Published: (2024)

Policy Gradient with Active Importance Sampling
by: Papini, Matteo, et al.
Published: (2024)

Towards Principled Unsupervised Multi-Agent Reinforcement Learning
by: Zamboni, Riccardo, et al.
Published: (2025)

Building surrogate models using trajectories of agents trained by Reinforcement Learning
by: Cestero, Julen, et al.
Published: (2025)

Unsupervised Behavioral Compression: Learning Low-Dimensional Policy Manifolds through State-Occupancy Matching
by: Fraschini, Andrea, et al.
Published: (2026)

No-Regret Reinforcement Learning in Smooth MDPs
by: Maran, Davide, et al.
Published: (2024)

Learning Deterministic Policies with Policy Gradients in Constrained Markov Decision Processes
by: Montenegro, Alessandro, et al.
Published: (2025)

Optimizing Energy Management of Smart Grid using Reinforcement Learning aided by Surrogate models built using Physics-informed Neural Networks
by: Cestero, Julen, et al.
Published: (2025)

Inverse Reinforcement Learning with Sub-optimal Experts
by: Poiani, Riccardo, et al.
Published: (2024)

Gym4ReaL: A Suite for Benchmarking Real-World Reinforcement Learning
by: Salaorni, Davide, et al.
Published: (2025)

Local Linearity: the Key for No-regret Reinforcement Learning in Continuous MDPs
by: Maran, Davide, et al.
Published: (2024)

Limitations of Physics-Informed Neural Networks: a Study on Smart Grid Surrogation
by: Cestero, Julen, et al.
Published: (2025)

Proximal Policy Optimization with Adaptive Exploration
by: Lixandru, Andrei
Published: (2024)

Help the machine to help you: an evaluation in the wild of egocentric data cleaning via skeptical learning
by: Bontempelli, Andrea, et al.
Published: (2025)

Parameterized Projected Bellman Operator
by: Vincent, Théo, et al.
Published: (2023)

Towards Provable Log Density Policy Gradient
by: Katdare, Pulkit, et al.
Published: (2024)

Actor-Critic with Active Importance Sampling
by: Molaei, Majid, et al.
Published: (2026)

Constrained Reinforcement Learning with Smoothed Log Barrier Function
by: Zhang, Baohe, et al.
Published: (2024)

Exploration Behavior of Untrained Policies
by: Adamczyk, Jacob
Published: (2025)

Do It for HER: First-Order Temporal Logic Reward Specification in Reinforcement Learning (Extended Version)
by: Olivieri, Pierriccardo, et al.
Published: (2026)

How to Allocate, How to Learn? Dynamic Rollout Allocation and Advantage Modulation for Policy Optimization
by: Fang, Yangyi, et al.
Published: (2026)

Unmasking On-Policy Distillation: Where It Helps, Where It Hurts, and Why
by: Armandpour, Mohammadreza, et al.
Published: (2026)

Categorical Policies: Multimodal Policy Learning and Exploration in Continuous Control
by: Islam, SM Mazharul, et al.
Published: (2025)

Nonsense Helps: Prompt Space Perturbation Broadens Reasoning Exploration
by: Huang, Langlin, et al.
Published: (2026)

On-Policy Optimization of ANFIS Policies Using Proximal Policy Optimization
by: Shankar, Kaaustaaub, et al.
Published: (2025)

Adaptive Exploration for Multi-Reward Multi-Policy Evaluation
by: Russo, Alessio, et al.
Published: (2025)

Safe Exploration via Policy Priors
by: Wendl, Manuel, et al.
Published: (2026)

How Far Can Fairness Constraints Help Recover From Biased Data?
by: Sharma, Mohit, et al.
Published: (2023)

Prompt Optimization with Logged Bandit Data
by: Kiyohara, Haruka, et al.
Published: (2025)

Post-Training with Policy Gradients: Optimality and the Base Model Barrier
by: Mousavi-Hosseini, Alireza, et al.
Published: (2026)

Pure Exploration under Mediators' Feedback
by: Poiani, Riccardo, et al.
Published: (2023)

Learning Social Heuristics for Human-Aware Path Planning
by: Eirale, Andrea, et al.
Published: (2025)

Exploration-Driven Policy Optimization in RLHF: Theoretical Insights on Efficient Data Utilization
by: Du, Yihan, et al.
Published: (2024)

Controllable Exploration in Hybrid-Policy RLVR for Multi-Modal Reasoning
by: Huang, Zhuoxu, et al.
Published: (2026)

Emergence of Exploration in Policy Gradient Reinforcement Learning via Retrying
by: Nishimori, Soichiro, et al.
Published: (2026)

APEX: Autonomous Policy Exploration for Self-Evolving LLM Agents
by: Li, Yibo, et al.
Published: (2026)