Cover Image

Action-Dependent Optimality-Preserving Reward Shaping

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Forbes, Grant C., Wang, Jianxun, Villalobos-Arias, Leonardo, Jhala, Arnav, Roberts, David L.
Format:	Preprint
Published:	2025
Subjects:	Machine Learning I.2.6
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Potential-Based Intrinsic Motivation: Preserving Optimality With Complex, Non-Markovian Shaping Rewards
by: Forbes, Grant C., et al.
Published: (2024)

Potential-Based Reward Shaping For Intrinsic Motivation
by: Forbes, Grant C., et al.
Published: (2024)

Fusing Rewards and Preferences in Reinforcement Learning
by: Khorasani, Sadegh, et al.
Published: (2025)

Rewarded Region Replay (R3) for Policy Learning with Discrete Action Space
by: Li, Bangzheng, et al.
Published: (2024)

Cost and Reward Infused Metric Elicitation
by: Bhateja, Chethan, et al.
Published: (2025)

LLM-Driven Intrinsic Motivation for Sparse Reward Reinforcement Learning
by: Quadros, André, et al.
Published: (2025)

Nonparametric Partial Disentanglement via Mechanism Sparsity: Sparse Actions, Interventions and Sparse Temporal Dependencies
by: Lachapelle, Sébastien, et al.
Published: (2024)

PRPO: Aligning Process Reward with Outcome Reward in Policy Optimization
by: Ding, Ruiyi, et al.
Published: (2026)

Exploring Neural Granger Causality with xLSTMs: Unveiling Temporal Dependencies in Complex Data
by: Poonia, Harsh, et al.
Published: (2025)

Graph Neural Network Based Action Ranking for Planning
by: Mangannavar, Rajesh, et al.
Published: (2024)

Uncertainty-Aware Reward Discounting for Mitigating Reward Hacking
by: Singha, Disha
Published: (2026)

Deep Memory Search: A Metaheuristic Approach for Optimizing Heuristic Search
by: Hedar, Abdel-Rahman, et al.
Published: (2024)

Difference Rewards Policy Gradients
by: Castellini, Jacopo, et al.
Published: (2020)

2Mamba2Furious: Linear in Complexity, Competitive in Accuracy
by: Mongaras, Gabriel, et al.
Published: (2026)

Contextual Combinatorial Bandits with Changing Action Sets via Gaussian Processes
by: Nika, Andi, et al.
Published: (2021)

Rewarding Beliefs, Not Actions: Consistency-Guided Credit Assignment for Long-Horizon Agents
by: Tang, Wenjie, et al.
Published: (2026)

AI and Machine Learning Approaches for Predicting Nanoparticles Toxicity The Critical Role of Physiochemical Properties
by: Yousaf, Iqra
Published: (2024)

Extrinsicaly Rewarded Soft Q Imitation Learning with Discriminator
by: Furuyama, Ryoma, et al.
Published: (2024)

DELTA: Variational Disentangled Learning for Privacy-Preserving Data Reprogramming
by: Malarkkan, Arun Vignesh, et al.
Published: (2025)

When Actions Disappear: Adversarial Action Removal in Self-Play Reinforcement Learning
by: Kujur, Arahan
Published: (2026)

Efficient Action-Constrained Reinforcement Learning via Acceptance-Rejection Method and Augmented MDPs
by: Hung, Wei, et al.
Published: (2025)

On the Generalization Gap in LLM Planning: Tests and Verifier-Reward RL
by: Belcamino, Valerio, et al.
Published: (2026)

Algebraic Machine Learning for Small-to-Medium Datasets Is Competitive against Strong Standard Baselines
by: Mendez, David, et al.
Published: (2026)

Getting ViT in Shape: Scaling Laws for Compute-Optimal Model Design
by: Alabdulmohsin, Ibrahim, et al.
Published: (2023)

A Constraint-Preserving Neural Network Approach for Solving Mean-Field Games Equilibrium
by: Liu, Jinwei, et al.
Published: (2025)

How VLAs Fail Differently: Black-Box Action Monitoring Reveals Architecture-Specific Failure Signatures
by: Gupta, Krishnam
Published: (2026)

RVI-SAC: Average Reward Off-Policy Deep Reinforcement Learning
by: Hisaki, Yukinari, et al.
Published: (2024)

Data-Incremental Continual Offline Reinforcement Learning
by: Gai, Sibo, et al.
Published: (2024)

Thread Detection and Response Generation using Transformers with Prompt Optimisation
by: T, Kevin Joshua, et al.
Published: (2024)

OER: Offline Experience Replay for Continual Offline Reinforcement Learning
by: Gai, Sibo, et al.
Published: (2023)

Representation learning with CGAN for casual inference
by: Weng, Zhaotian, et al.
Published: (2024)

HGCN(O): A Self-Tuning GCN HyperModel Toolkit for Outcome Prediction in Event-Sequence Data
by: Wang, Fang, et al.
Published: (2025)

Decoding Rewards in Competitive Games: Inverse Game Theory with Entropy Regularization
by: Liao, Junyi, et al.
Published: (2026)

The Bayesian Confidence (BACON) Estimator for Deep Neural Networks
by: Kee, Patrick D., et al.
Published: (2024)

Explainable Graph Representation Learning via Graph Pattern Analysis
by: Wang, Xudong, et al.
Published: (2025)

Improving the Expressiveness of $K$-hop Message-Passing GNNs by Injecting Contextualized Substructure Information
by: Yao, Tianjun, et al.
Published: (2024)

Evaluating and Learning Robust Bandit Policies Under Uncertain Causal Mechanisms
by: Avery, Katherine, et al.
Published: (2025)

New Paradigm of Adversarial Training: Releasing Accuracy-Robustness Trade-Off via Dummy Class
by: Wang, Yanyun, et al.
Published: (2024)

Safe Reinforcement Learning with Preference-based Constraint Inference
by: Li, Chenglin, et al.
Published: (2026)

Graceful task adaptation with a bi-hemispheric RL agent
by: Nicholas, Grant, et al.
Published: (2024)