Analyzing and Bridging the Gap between Maximizing Total Reward and Discounted Reward in Deep Reinforcement Learning
Fuente:
arXiv
Saved in:
| Main Authors: | Yin, Shuyu, Wen, Fei, Liu, Peilin, Luo, Tao |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Probing Implicit Bias in Semi-gradient Q-learning: Visualizing the Effective Loss Landscapes via the Fokker--Planck Equation
by: Yin, Shuyu, et al.
Published: (2024)
by: Yin, Shuyu, et al.
Published: (2024)
A priori Estimates for Deep Residual Network in Continuous-time Reinforcement Learning
by: Yin, Shuyu, et al.
Published: (2024)
by: Yin, Shuyu, et al.
Published: (2024)
Reinforcement Learning for Infinite-Horizon Average-Reward Linear MDPs via Approximation by Discounted-Reward MDPs
by: Hong, Kihyuk, et al.
Published: (2024)
by: Hong, Kihyuk, et al.
Published: (2024)
Binary Reward Labeling: Bridging Offline Preference and Reward-Based Reinforcement Learning
by: Xu, Yinglun, et al.
Published: (2024)
by: Xu, Yinglun, et al.
Published: (2024)
Risk-Averse Total-Reward Reinforcement Learning
by: Su, Xihong, et al.
Published: (2025)
by: Su, Xihong, et al.
Published: (2025)
Bridging the Gap Between Average and Discounted TD Learning
by: Tian, Haoxing, et al.
Published: (2026)
by: Tian, Haoxing, et al.
Published: (2026)
Adaptive Segment-level Reward: Bridging the Gap Between Action and Reward Space in Alignment
by: Li, Yanshi, et al.
Published: (2024)
by: Li, Yanshi, et al.
Published: (2024)
Uncertainty-Aware Reward Discounting for Mitigating Reward Hacking
by: Singha, Disha
Published: (2026)
by: Singha, Disha
Published: (2026)
Effective Reward Specification in Deep Reinforcement Learning
by: Roy, Julien
Published: (2024)
by: Roy, Julien
Published: (2024)
Text2Reward: Reward Shaping with Language Models for Reinforcement Learning
by: Xie, Tianbao, et al.
Published: (2023)
by: Xie, Tianbao, et al.
Published: (2023)
Reducing Reward Dependence in RL Through Adaptive Confidence Discounting
by: Satici, Muhammed Yusuf, et al.
Published: (2025)
by: Satici, Muhammed Yusuf, et al.
Published: (2025)
Deep Reinforcement Learning with Hybrid Intrinsic Reward Model
by: Yuan, Mingqi, et al.
Published: (2025)
by: Yuan, Mingqi, et al.
Published: (2025)
Explicit Mutual Information Maximization for Self-Supervised Learning
by: Chang, Lele, et al.
Published: (2024)
by: Chang, Lele, et al.
Published: (2024)
Revisiting Value Iteration: Unified Analysis of Discounted and Average-Reward Cases
by: Mustafin, Arsenii, et al.
Published: (2025)
by: Mustafin, Arsenii, et al.
Published: (2025)
Reinforcement Learning from Bagged Reward
by: Tang, Yuting, et al.
Published: (2024)
by: Tang, Yuting, et al.
Published: (2024)
Towards Bridging the Reward-Generation Gap in Direct Alignment Algorithms
by: Xiao, Zeguan, et al.
Published: (2025)
by: Xiao, Zeguan, et al.
Published: (2025)
Reward-Conditioned Reinforcement Learning
by: Nauman, Michal, et al.
Published: (2026)
by: Nauman, Michal, et al.
Published: (2026)
Reward Under Attack: Analyzing the Robustness and Hackability of Process Reward Models
by: Tiwari, Rishabh, et al.
Published: (2026)
by: Tiwari, Rishabh, et al.
Published: (2026)
Reward Models in Deep Reinforcement Learning: A Survey
by: Yu, Rui, et al.
Published: (2025)
by: Yu, Rui, et al.
Published: (2025)
The Distributional Reward Critic Framework for Reinforcement Learning Under Perturbed Rewards
by: Chen, Xi, et al.
Published: (2024)
by: Chen, Xi, et al.
Published: (2024)
Bridging the Human to Robot Dexterity Gap through Object-Oriented Rewards
by: Guzey, Irmak, et al.
Published: (2024)
by: Guzey, Irmak, et al.
Published: (2024)
Focal Reward: Balanced Reinforcement Learning under Rubric-Based Rewards
by: Huang, Yu, et al.
Published: (2026)
by: Huang, Yu, et al.
Published: (2026)
Contextual Rollout Bandits for Reinforcement Learning with Verifiable Rewards
by: Lu, Xiaodong, et al.
Published: (2026)
by: Lu, Xiaodong, et al.
Published: (2026)
Generalization in Deep Reinforcement Learning for Robotic Navigation by Reward Shaping
by: Miranda, Victor R. F., et al.
Published: (2022)
by: Miranda, Victor R. F., et al.
Published: (2022)
Closing the Gap between TD Learning and Supervised Learning with $Q$-Conditioned Maximization
by: Lei, Xing, et al.
Published: (2025)
by: Lei, Xing, et al.
Published: (2025)
ELO-Rated Sequence Rewards: Advancing Reinforcement Learning Models
by: Ju, Qi, et al.
Published: (2024)
by: Ju, Qi, et al.
Published: (2024)
Reward-Zero: Language Embedding Driven Implicit Reward Mechanisms for Reinforcement Learning
by: Zhang, Heng, et al.
Published: (2026)
by: Zhang, Heng, et al.
Published: (2026)
The Value of Reward Lookahead in Reinforcement Learning
by: Merlis, Nadav, et al.
Published: (2024)
by: Merlis, Nadav, et al.
Published: (2024)
Informativeness of Reward Functions in Reinforcement Learning
by: Devidze, Rati, et al.
Published: (2024)
by: Devidze, Rati, et al.
Published: (2024)
To the Max: Reinventing Reward in Reinforcement Learning
by: Veviurko, Grigorii, et al.
Published: (2024)
by: Veviurko, Grigorii, et al.
Published: (2024)
Reward Design for Reinforcement Learning Agents
by: Devidze, Rati
Published: (2025)
by: Devidze, Rati
Published: (2025)
Diffusion Classifier-Driven Reward for Offline Preference-based Reinforcement Learning
by: Pang, Teng, et al.
Published: (2025)
by: Pang, Teng, et al.
Published: (2025)
Learning Guarantee of Reward Modeling Using Deep Neural Networks
by: Luo, Yuanhang, et al.
Published: (2025)
by: Luo, Yuanhang, et al.
Published: (2025)
Constraints as Rewards: Reinforcement Learning for Robots without Reward Functions
by: Ishihara, Yu, et al.
Published: (2025)
by: Ishihara, Yu, et al.
Published: (2025)
Maximally Permissive Reward Machines
by: Varricchione, Giovanni, et al.
Published: (2024)
by: Varricchione, Giovanni, et al.
Published: (2024)
Beyond Simple Sum of Delayed Rewards: Non-Markovian Reward Modeling for Reinforcement Learning
by: Tang, Yuting, et al.
Published: (2024)
by: Tang, Yuting, et al.
Published: (2024)
Towards High Data Efficiency in Reinforcement Learning with Verifiable Reward
by: Tang, Xinyu, et al.
Published: (2025)
by: Tang, Xinyu, et al.
Published: (2025)
Tactical Decision Making for Autonomous Trucks by Deep Reinforcement Learning with Total Cost of Operation Based Reward
by: Pathare, Deepthi, et al.
Published: (2024)
by: Pathare, Deepthi, et al.
Published: (2024)
Multi-Objective and Mixed-Reward Reinforcement Learning via Reward-Decorrelated Policy Optimization
by: Bai, Yang, et al.
Published: (2026)
by: Bai, Yang, et al.
Published: (2026)
Code as Reward: Empowering Reinforcement Learning with VLMs
by: Venuto, David, et al.
Published: (2024)
by: Venuto, David, et al.
Published: (2024)
Similar Items
-
Probing Implicit Bias in Semi-gradient Q-learning: Visualizing the Effective Loss Landscapes via the Fokker--Planck Equation
by: Yin, Shuyu, et al.
Published: (2024) -
A priori Estimates for Deep Residual Network in Continuous-time Reinforcement Learning
by: Yin, Shuyu, et al.
Published: (2024) -
Reinforcement Learning for Infinite-Horizon Average-Reward Linear MDPs via Approximation by Discounted-Reward MDPs
by: Hong, Kihyuk, et al.
Published: (2024) -
Binary Reward Labeling: Bridging Offline Preference and Reward-Based Reinforcement Learning
by: Xu, Yinglun, et al.
Published: (2024) -
Risk-Averse Total-Reward Reinforcement Learning
by: Su, Xihong, et al.
Published: (2025)