Copertina

What if Pinocchio Were a Reinforcement Learning Agent: A Normative End-to-End Pipeline

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autore principale:	Alcaraz, Benoît
Natura:	Preprint
Pubblicazione:	2026
Soggetti:	Artificial Intelligence Multiagent Systems
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Dialogue Diplomats: An End-to-End Multi-Agent Reinforcement Learning System for Automated Conflict Resolution and Consensus Building
di: Bolleddu, Deepak
Pubblicazione: (2025)

Learning to Communicate: Toward End-to-End Optimization of Multi-Agent Language Systems
di: Yu, Ye, et al.
Pubblicazione: (2026)

Collision Avoidance and Navigation for a Quadrotor Swarm Using End-to-end Deep Reinforcement Learning
di: Huang, Zhehui, et al.
Pubblicazione: (2023)

LC-Opt: Benchmarking Reinforcement Learning and Agentic AI for End-to-End Liquid Cooling Optimization in Data Centers
di: Naug, Avisek, et al.
Pubblicazione: (2025)

UCAgent: An End-to-End Agent for Block-Level Functional Verification
di: Wang, Junyue, et al.
Pubblicazione: (2026)

Multicopy Reinforcement Learning Agents
di: Wolfe, Alicia P., et al.
Pubblicazione: (2023)

Doctorina MedBench: End-to-End Evaluation of Agent-Based Medical AI
di: Kozlova, Anna, et al.
Pubblicazione: (2026)

Manalyzer: End-to-end Automated Meta-analysis with Multi-agent System
di: Xu, Wanghan, et al.
Pubblicazione: (2025)

Heterogeneity in Multi-Agent Reinforcement Learning
di: Hu, Tianyi, et al.
Pubblicazione: (2025)

Vulnerable Agent Identification in Large-Scale Multi-Agent Reinforcement Learning
di: Li, Simin, et al.
Pubblicazione: (2025)

Scalable Safe Multi-Agent Reinforcement Learning for Multi-Agent System
di: Du, Haikuo, et al.
Pubblicazione: (2025)

Can AI Agents Design and Implement Drug Discovery Pipelines?
di: Smbatyan, Khachik, et al.
Pubblicazione: (2025)

MADP: A Multi-Agent Pipeline for Sustainable Document Processing with Human-in-the-Loop
di: Gosmar, Diego, et al.
Pubblicazione: (2026)

MLZero: A Multi-Agent System for End-to-end Machine Learning Automation
di: Fang, Haoyang, et al.
Pubblicazione: (2025)

Memory-Augmented Reinforcement Learning Agent for CAD Generation
di: Xiaolong, Yin, et al.
Pubblicazione: (2026)

Measuring Policy Distance for Multi-Agent Reinforcement Learning
di: Hu, Tianyi, et al.
Pubblicazione: (2024)

Multi-Agent Reinforcement Learning with Communication-Constrained Priors
di: Yang, Guang, et al.
Pubblicazione: (2025)

Causal Mean Field Multi-Agent Reinforcement Learning
di: Ma, Hao, et al.
Pubblicazione: (2025)

Agent-as-Tool: A Study on the Hierarchical Decision Making with Reinforcement Learning
di: Zhang, Yanfei
Pubblicazione: (2025)

WebTestBench: Evaluating Computer-Use Agents towards End-to-End Automated Web Testing
di: Kong, Fanheng, et al.
Pubblicazione: (2026)

Multi-Agent Reinforcement Learning Simulation for Environmental Policy Synthesis
di: Rudd-Jones, James, et al.
Pubblicazione: (2025)

SocialGFs: Learning Social Gradient Fields for Multi-Agent Reinforcement Learning
di: Long, Qian, et al.
Pubblicazione: (2024)

Fair Compromises in Participatory Budgeting: a Multi-Agent Deep Reinforcement Learning Approach
di: Adams, Hugh, et al.
Pubblicazione: (2025)

Multi-source Plume Tracing via Multi-Agent Reinforcement Learning
di: Granadeno, Pedro Antonio Alarcon, et al.
Pubblicazione: (2025)

Multi-Agent Reinforcement Learning for Market Making: Competition without Collusion
di: Wang, Ziyi, et al.
Pubblicazione: (2025)

Constructive Conflict-Driven Multi-Agent Reinforcement Learning for Strategic Diversity
di: Mai, Yuxiang, et al.
Pubblicazione: (2025)

Multi-Agent Target Assignment and Path Finding for Intelligent Warehouse: A Cooperative Multi-Agent Deep Reinforcement Learning Perspective
di: Liu, Qi, et al.
Pubblicazione: (2024)

PyTSC: A Unified Platform for Multi-Agent Reinforcement Learning in Traffic Signal Control
di: Bokade, Rohit, et al.
Pubblicazione: (2024)

Trust-Based Social Learning for Communication (TSLEC) Protocol Evolution in Multi-Agent Reinforcement Learning
di: Weinberg, Abraham Itzhak
Pubblicazione: (2025)

Achieving Equilibrium under Utility Heterogeneity: An Agent-Attention Framework for Multi-Agent Multi-Objective Reinforcement Learning
di: Li, Zhuhui, et al.
Pubblicazione: (2025)

Quality-Aware Exploration Budget Allocation for Cooperative Multi-Agent Reinforcement Learning
di: Oh, Dahyun, et al.
Pubblicazione: (2026)

ARMS: Automatic Reward Shaping for Sparse-Reward Multi-Agent Reinforcement Learning
di: Abboud, Elie, et al.
Pubblicazione: (2026)

Graph Based Deep Reinforcement Learning Aided by Transformers for Multi-Agent Cooperation
di: Elrod, Michael, et al.
Pubblicazione: (2025)

Joint Intrinsic Motivation for Coordinated Exploration in Multi-Agent Deep Reinforcement Learning
di: Toquebiau, Maxime, et al.
Pubblicazione: (2024)

Contextual Knowledge Sharing in Multi-Agent Reinforcement Learning with Decentralized Communication and Coordination
di: Du, Hung, et al.
Pubblicazione: (2025)

Toward Dependency Dynamics in Multi-Agent Reinforcement Learning for Traffic Signal Control
di: Zhang, Yuli, et al.
Pubblicazione: (2025)

Towards Generalizability of Multi-Agent Reinforcement Learning in Graphs with Recurrent Message Passing
di: Weil, Jannis, et al.
Pubblicazione: (2024)

What Is Your Agent's GPA? A Framework for Evaluating Agent Goal-Plan-Action Alignment
di: Jia, Allison Sihan, et al.
Pubblicazione: (2025)

Cooperation and Fairness in Multi-Agent Reinforcement Learning
di: Aloor, Jasmine Jerry, et al.
Pubblicazione: (2024)

Multi-Agent Reinforcement Learning for Autonomous Driving: A Survey
di: Zhang, Ruiqi, et al.
Pubblicazione: (2024)