Imagen de Portada

ProgAgent:A Continual RL Agent with Progress-Aware Rewards

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Tan, Jinzhou, Adineera, Gabriel, Kim, Jinoh
Formato:	Preprint
Publicado:	2026
Materias:	Machine Learning Artificial Intelligence
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

ResWM: Residual-Action World Model for Visual RL
por: Zhang, Jseen, et al.
Publicado: (2026)

ProgRM: Build Better GUI Agents with Progress Rewards
por: Zhang, Danyang, et al.
Publicado: (2025)

ProgFed: Effective, Communication, and Computation Efficient Federated Learning by Progressive Training
por: Wang, Hui-Po, et al.
Publicado: (2021)

Debate as Reward: A Multi-Agent Reward System for Scientific Ideation via RL Post-Training
por: Salimi, Moein, et al.
Publicado: (2026)

Towards Improving Reward Design in RL: A Reward Alignment Metric for RL Practitioners
por: Muslimani, Calarina, et al.
Publicado: (2025)

Capacity-Aware Planning and Scheduling in Budget-Constrained Multi-Agent MDPs: A Meta-RL Approach
por: Vora, Manav, et al.
Publicado: (2024)

Meta-RL Induces Exploration in Language Agents
por: Jiang, Yulun, et al.
Publicado: (2025)

Accelerating Diffusion Planners in Offline RL via Reward-Aware Consistency Trajectory Distillation
por: Duan, Xintong, et al.
Publicado: (2025)

RDAR: Reward-Driven Agent Relevance Estimation for Autonomous Driving
por: Bosio, Carlo, et al.
Publicado: (2025)

RF-Agent: Automated Reward Function Design via Language Agent Tree Search
por: Gao, Ning, et al.
Publicado: (2026)

ArenaRL: Scaling RL for Open-Ended Agents via Tournament-based Relative Ranking
por: Zhang, Qiang, et al.
Publicado: (2026)

ProgCo: Program Helps Self-Correction of Large Language Models
por: Song, Xiaoshuai, et al.
Publicado: (2025)

AgentRM: Enhancing Agent Generalization with Reward Modeling
por: Xia, Yu, et al.
Publicado: (2025)

Unraveling the Complexity of Memory in RL Agents: an Approach for Classification and Evaluation
por: Cherepanov, Egor, et al.
Publicado: (2024)

Mind the Model, Not the Agent: The Primacy Bias in Model-based RL
por: Qiao, Zhongjian, et al.
Publicado: (2023)

Proto Successor Measure: Representing the Behavior Space of an RL Agent
por: Agarwal, Siddhant, et al.
Publicado: (2024)

RewardFlow: Topology-Aware Reward Propagation on State Graphs for Agentic RL with Large Language Models
por: Feng, Xiao, et al.
Publicado: (2026)

FlickerFusion: Intra-trajectory Domain Generalizing Multi-Agent RL
por: Koh, Woosung, et al.
Publicado: (2024)

Analysis of the Memorization and Generalization Capabilities of AI Agents: Are Continual Learners Robust?
por: Kim, Minsu, et al.
Publicado: (2023)

Reward Sharpness-Aware Fine-Tuning for Diffusion Models
por: Kim, Kwanyoung, et al.
Publicado: (2026)

MobileRL: Online Agentic Reinforcement Learning for Mobile GUI Agents
por: Xu, Yifan, et al.
Publicado: (2025)

Which Experiences Are Influential for RL Agents? Efficiently Estimating The Influence of Experiences
por: Hiraoka, Takuya, et al.
Publicado: (2024)

Process Reward Models for LLM Agents: Practical Framework and Directions
por: Choudhury, Sanjiban
Publicado: (2025)

Online Continual Learning For Interactive Instruction Following Agents
por: Kim, Byeonghwi, et al.
Publicado: (2024)

Adaptive Milestone Reward for GUI Agents
por: Zheng, Congmin, et al.
Publicado: (2026)

LeakAgent: RL-based Red-teaming Agent for LLM Privacy Leakage
por: Nie, Yuzhou, et al.
Publicado: (2024)

ProgVLA: Progress-Aware Robot Manipulation Skill Learning
por: Kim, Seungsu, et al.
Publicado: (2026)

AgentRewardBench: Evaluating Automatic Evaluations of Web Agent Trajectories
por: Lù, Xing Han, et al.
Publicado: (2025)

Your Reward Function for RL is Your Best PRM for Search: Unifying RL and Search-Based TTS
por: Jin, Can, et al.
Publicado: (2025)

EnterpriseBench Corecraft: Training Generalizable Agents on High-Fidelity RL Environments
por: Mehta, Sushant, et al.
Publicado: (2026)

Plan Before You Trade: Inference-Time Optimization for RL Trading Agents
por: Go, Eun, et al.
Publicado: (2026)

LLMs are Greedy Agents: Effects of RL Fine-tuning on Decision-Making Abilities
por: Schmied, Thomas, et al.
Publicado: (2025)

Reward Hacking Benchmark: Measuring Exploits in LLM Agents with Tool Use
por: Thaman, Kunvar
Publicado: (2026)

MAESTRO: Multi-Agent Environment Shaping through Task and Reward Optimization
por: Wu, Boyuan
Publicado: (2025)

Verifying Meta-Awareness via Predictive Rewards in Reasoning Models
por: Kim, Yoonjeon, et al.
Publicado: (2025)

AgentGA: Evolving Code Solutions in Agent-Seed Space
por: Tan, David Y. Y., et al.
Publicado: (2026)

Agent-Omit: Adaptive Context Omission for Efficient LLM Agents
por: Ning, Yansong, et al.
Publicado: (2026)

Spatially-Aware Transformer for Embodied Agents
por: Cho, Junmo, et al.
Publicado: (2024)

FairAgent: Democratizing Fairness-Aware Machine Learning with LLM-Powered Agents
por: Dai, Yucong, et al.
Publicado: (2025)

Multi-Objective Instruction-Aware Representation Learning in Procedural Content Generation RL
por: Kim, Sung-Hyun, et al.
Publicado: (2025)