Copertina

Learning State-Dependent Policy Parametrizations for Dynamic Technician Routing with Rework

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Stein, Jonas, Hildebrandt, Florentin D, Thomas, Barrett W, Ulmer, Marlin W
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Artificial Intelligence
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

The Restaurant Meal Delivery Problem with Ghost Kitchens
di: Neria, Gal, et al.
Pubblicazione: (2024)

Shaping Decision Models for Stochastic Dynamic Optimization Problems via Reinforcement Learning
di: Florentin D. Hildebrandt, et al.
Pubblicazione: (2026)

Management Decisions in Manufacturing using Causal Machine Learning -- To Rework, or not to Rework?
di: Schwarz, Philipp, et al.
Pubblicazione: (2024)

To Start Up a Start-Up$-$Embedding Strategic Demand Development in Operational On-Demand Fulfillment via Reinforcement Learning with Information Shaping
di: Chen, Xinwei, et al.
Pubblicazione: (2025)

A Cost Function Approximation Based Large Neighborhood Search for Dynamic Medical Courier Services
di: Jarmo Haferkamp, et al.
Pubblicazione: (2025)

Enhancing Adaptive Behavioral Interventions with LLM Inference from Participant-Described States
di: Karine, Karine, et al.
Pubblicazione: (2025)

Leveraging GPT-4o Efficiency for Detecting Rework Anomaly in Business Processes
di: Derakhshan, Mohammad, et al.
Pubblicazione: (2025)

Beyond State-Wise Mirror Descent: Offline Policy Optimization with Parametric Policies
di: Li, Xiang, et al.
Pubblicazione: (2026)

Memory-Enhanced Neural Solvers for Routing Problems
di: Chalumeau, Felix, et al.
Pubblicazione: (2024)

What does a system modify when it modifies itself?
di: Koch, Florentin
Pubblicazione: (2026)

From indicators to biology: the calibration problem in artificial consciousness
di: Koch, Florentin
Pubblicazione: (2026)

StepCountJITAI: simulation environment for RL with application to physical activity adaptive intervention
di: Karine, Karine, et al.
Pubblicazione: (2024)

Combining LLM decision and RL action selection to improve RL policy for adaptive interventions
di: Karine, Karine, et al.
Pubblicazione: (2025)

On Uncertainty In Natural Language Processing
di: Ulmer, Dennis
Pubblicazione: (2024)

Reworking the Computer Age
Pubblicazione: (2026)

Heteroscedastic Temporal Variational Autoencoder For Irregular Time Series
di: Shukla, Satya Narayan, et al.
Pubblicazione: (2021)

Resilient Routing: Risk-Aware Dynamic Routing in Smart Logistics via Spatiotemporal Graph Learning
di: Xue, Zhiming, et al.
Pubblicazione: (2026)

Data-Efficient Safe Policy Improvement Using Parametric Structure
di: Engelen, Kasper, et al.
Pubblicazione: (2025)

A Dynamic Survey of Soft Set Theory and Its Extensions
di: Fujita, Takaaki, et al.
Pubblicazione: (2026)

A Generic Machine Learning Framework for Fully-Unsupervised Anomaly Detection with Contaminated Data
di: Ulmer, Markus, et al.
Pubblicazione: (2023)

Recursivism: An Artistic Paradigm for Self-Transforming Art in the Age of AI
di: Koch, Florentin
Pubblicazione: (2026)

Self-Routing: Parameter-Free Expert Routing from Hidden States
di: Mohamud, Jama Hussein, et al.
Pubblicazione: (2026)

Policy Regularization on Globally Accessible States in Cross-Dynamics Reinforcement Learning
di: Xue, Zhenghai, et al.
Pubblicazione: (2025)

Fuzzy, Neutrosophic, and Uncertain Graph Theory: Properties and Applications
di: Fujita, Takaaki, et al.
Pubblicazione: (2026)

Learning Coordinated Bimanual Manipulation Policies using State Diffusion and Inverse Dynamics Models
di: Chen, Haonan, et al.
Pubblicazione: (2025)

Combinatorial Optimization with Policy Adaptation using Latent Space Search
di: Chalumeau, Felix, et al.
Pubblicazione: (2023)

Unveiling Privacy Policy Complexity: An Exploratory Study Using Graph Mining, Machine Learning, and Natural Language Processing
di: Ramasamy, Vijayalakshmi, et al.
Pubblicazione: (2025)

AI Technicians: Developing Rapid Occupational Training Methods for a Competitive AI Workforce
di: Savelka, Jaromir, et al.
Pubblicazione: (2025)

Policy-Guided Stepwise Model Routing for Cost-Effective Reasoning
di: Si, Wenwen, et al.
Pubblicazione: (2026)

Promoting Two-sided Fairness in Dynamic Vehicle Routing Problem
di: Kang, Yufan, et al.
Pubblicazione: (2024)

BOTS: Batch Bayesian Optimization of Extended Thompson Sampling for Severely Episode-Limited RL Settings
di: Karine, Karine, et al.
Pubblicazione: (2024)

State Transfer Reveals Reuse in Controlled Routing
di: Lu, Yanzhen, et al.
Pubblicazione: (2026)

A Dynamic Survey of Fuzzy, Intuitionistic Fuzzy, Neutrosophic, Plithogenic, and Extensional Sets
di: Fujita, Takaaki, et al.
Pubblicazione: (2026)

Learning Lifted Action Models From Traces of Incomplete Actions and States
di: Jansen, Niklas, et al.
Pubblicazione: (2025)

Quantum Optimization Algorithms
di: Stein, Jonas, et al.
Pubblicazione: (2025)

Certifiably Robust Policies for Uncertain Parametric Environments
di: Schnitzer, Yannik, et al.
Pubblicazione: (2024)

State Design Matters: How Representations Shape Dynamic Reasoning in Large Language Models
di: Wong, Annie, et al.
Pubblicazione: (2026)

Preserve Support, Not Correspondence: Dynamic Routing for Offline Reinforcement Learning
di: Mu, Zhancun, et al.
Pubblicazione: (2026)

Dynamic Replanning for Improved Public Transport Routing
di: Abuaisha, Abdallah, et al.
Pubblicazione: (2025)

Learning with Foresight: Enhancing Neural Routing Policy via Multi-Node Lookahead Prediction
di: Jiang, Xia, et al.
Pubblicazione: (2026)