:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Niu, Xuecheng, Ito, Akinori, Nose, Takashi
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Artificial Intelligence
Online Access:	https://arxiv.org/abs/2402.00085
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

CDE: Curiosity-Driven Exploration for Efficient Reinforcement Learning in Large Language Models
by: Dai, Runpeng, et al.
Published: (2025)

Diversifying Policy Behaviors with Extrinsic Behavioral Curiosity
by: Wan, Zhenglin, et al.
Published: (2024)

Predictive Safety Shield for Dyna-Q Reinforcement Learning
by: Pin, Jin, et al.
Published: (2025)

Curiosity-Diffuser: Curiosity Guide Diffusion Models for Reliability
by: Liu, Zihao, et al.
Published: (2025)

In-Context Curiosity: Distilling Exploration for Decision-Pretrained Transformers on Bandit Tasks
by: Yang, Huitao, et al.
Published: (2025)

Efficient On-Policy Reinforcement Learning via Exploration of Sparse Parameter Space
by: Zhang, Xinyu, et al.
Published: (2025)

Physics-Informed Model and Hybrid Planning for Efficient Dyna-Style Reinforcement Learning
by: Asri, Zakariae El, et al.
Published: (2024)

Safe-Support Q-Learning: Learning without Unsafe Exploration
by: Lim, Yeeun, et al.
Published: (2026)

A Deep Q-Learning based Smart Scheduling of EVs for Demand Response in Smart Grids
by: Chifu, Viorica Rozina, et al.
Published: (2024)

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

Using Curiosity for an Even Representation of Tasks in Continual Offline Reinforcement Learning
by: Pathmanathan, Pankayaraj, et al.
Published: (2023)

Confidence-Controlled Exploration: Efficient Sparse-Reward Policy Learning for Robot Navigation
by: Patel, Bhrij, et al.
Published: (2023)

Curiosity-driven RL for symbolic equation solving
by: O'Keeffe, Kevin P.
Published: (2025)

Pruning the Way to Reliable Policies: A Multi-Objective Deep Q-Learning Approach to Critical Care
by: Shirali, Ali, et al.
Published: (2023)

Satisficing Exploration for Deep Reinforcement Learning
by: Arumugam, Dilip, et al.
Published: (2024)

Dynamic Neural Curiosity Enhances Learning Flexibility for Autonomous Goal Discovery
by: Houbre, Quentin, et al.
Published: (2024)

Curiosity & Entropy Driven Unsupervised RL in Multiple Environments
by: Dewan, Shaurya, et al.
Published: (2024)

Artificial Agency Program: Curiosity, compression, and communication in agents
by: Csaky, Richard
Published: (2026)

Efficient Deep Reinforcement Learning with Predictive Processing Proximal Policy Optimization
by: Küçükoğlu, Burcu, et al.
Published: (2022)

Improving Offline-to-Online Reinforcement Learning with Q Conditioned State Entropy Exploration
by: Zhang, Ziqi, et al.
Published: (2023)

Efficient Diversity-based Experience Replay for Deep Reinforcement Learning
by: Zhao, Kaiyan, et al.
Published: (2024)

Is Exploration or Optimization the Problem for Deep Reinforcement Learning?
by: Berseth, Glen
Published: (2025)

Per-Domain Generalizing Policies: On Learning Efficient and Robust Q-Value Functions (Extended Version with Technical Appendix)
by: Müller, Nicola J., et al.
Published: (2026)

Unsupervised Learning of Efficient Exploration: Pre-training Adaptive Policies via Self-Imposed Goals
by: Pappalardo, Octavio
Published: (2026)

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

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

Learning from Relevant Subgoals in Successful Dialogs using Iterative Training for Task-oriented Dialog Systems
by: Kaiser, Magdalena, et al.
Published: (2024)

Uncertainty Makes It Stable: Curiosity-Driven Quantized Mixture-of-Experts
by: Ordóñez, Sebastián Andrés Cajas, et al.
Published: (2025)

Guided Exploration for Efficient Relational Model Learning
by: Feng, Annie, et al.
Published: (2025)

Adventurer: Exploration with BiGAN for Deep Reinforcement Learning
by: Liu, Yongshuai, et al.
Published: (2025)

Functional Critics Are Essential for Actor-Critic: From Off-Policy Stability to Efficient Exploration
by: Bai, Qinxun, et al.
Published: (2025)

Residual Q-Learning: Offline and Online Policy Customization without Value
by: Li, Chenran, et al.
Published: (2023)

Q-Flow: Stable and Expressive Reinforcement Learning with Flow-Based Policy
by: Doo, JaeHyeok, et al.
Published: (2026)

Optimistic World Models: Efficient Exploration in Model-Based Deep Reinforcement Learning
by: Mete, Akshay, et al.
Published: (2026)

An Optimal Policy for Learning Controllable Dynamics by Exploration
by: Loxley, Peter N.
Published: (2025)

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

Q-Policy: Quantum-Enhanced Policy Evaluation for Scalable Reinforcement Learning
by: Cherukuri, Kalyan, et al.
Published: (2025)

Deep Reinforcement Learning Guided Improvement Heuristic for Job Shop Scheduling
by: Zhang, Cong, et al.
Published: (2022)

$β$-DQN: Improving Deep Q-Learning By Evolving the Behavior
by: Zhang, Hongming, et al.
Published: (2025)

Priors Matter: Addressing Misspecification in Bayesian Deep Q-Learning
by: van der Vaart, Pascal R., et al.
Published: (2025)