Copertina

Large-Scale Continual Scheduling and Execution for Dynamic Distributed Satellite Constellation Observation Allocation

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Zilberstein, Itai, Chien, Steve
Natura:	Preprint
Pubblicazione:	2026
Soggetti:	Artificial Intelligence
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Dynamic Targeting of Satellite Observations Using Supplemental Geostationary Satellite Data and Hierarchical Planning
di: Kangaslahti, Akseli, et al.
Pubblicazione: (2026)

Real-Time Instrument Planning and Perception for Novel Measurements of Dynamic Phenomena
di: Zilberstein, Itai, et al.
Pubblicazione: (2025)

Learning-Based Planning for Improving Science Return of Earth Observation Satellites
di: Breitfeld, Abigail, et al.
Pubblicazione: (2025)

Demonstrating Onboard Inference for Earth Science Applications with Spectral Analysis Algorithms and Deep Learning
di: Zilberstein, Itai, et al.
Pubblicazione: (2025)

Learning Potentials for Dynamic Matching and Application to Heart Transplantation
di: Zilberstein, Itai, et al.
Pubblicazione: (2026)

Near-Optimal Dynamic Matching via Coarsening with Application to Heart Transplantation
di: Zilberstein, Itai, et al.
Pubblicazione: (2026)

Resource Allocation and Workload Scheduling for Large-Scale Distributed Deep Learning: A Survey
di: Liang, Feng, et al.
Pubblicazione: (2024)

On the Role of AI in Managing Satellite Constellations: Insights from the ConstellAI Project
di: Stock, Gregory F., et al.
Pubblicazione: (2025)

Is Four Enough? Automated Reasoning Approaches and Dual Bounds for Condorcet Dimensions of Elections
di: Zilberstein, Itai, et al.
Pubblicazione: (2026)

Continued AI Scaling Requires Repeated Efficiency Doublings
di: Lu, Chien-Ping
Pubblicazione: (2026)

An energy-efficient learning solution for the Agile Earth Observation Satellite Scheduling Problem
di: Mercado-Martínez, Antonio M., et al.
Pubblicazione: (2025)

Optimizing Earth Observation Satellite Schedules under Unknown Operational Constraints: An Active Constraint Acquisition Approach
di: Belaid, Mohamed-Bachir
Pubblicazione: (2026)

Earth Observation Satellite Scheduling with Graph Neural Networks and Monte Carlo Tree Search
di: Jacquet, Antoine, et al.
Pubblicazione: (2024)

Collaborative Space Object Detection with Multi-Satellite Viewpoints in LEO Constellations
di: Qu, Xingyu, et al.
Pubblicazione: (2026)

Distributed Multi-Agent Coordination Using Multi-Modal Foundation Models
di: Mahmud, Saaduddin, et al.
Pubblicazione: (2025)

MAPLE: A Framework for Active Preference Learning Guided by Large Language Models
di: Mahmud, Saaduddin, et al.
Pubblicazione: (2024)

On-Orbit Space AI: Federated, Multi-Agent, and Collaborative Algorithms for Satellite Constellations
di: Wang, Ziyang
Pubblicazione: (2026)

Constellation as a Service: Tailored Connectivity Management in Direct-Satellite-to-Device Networks
di: Wang, Feng, et al.
Pubblicazione: (2025)

Reinforcement Learning-enabled Satellite Constellation Reconfiguration and Retasking for Mission-Critical Applications
di: Alami, Hassan El, et al.
Pubblicazione: (2024)

Approximate Estimation of High-dimension Execution Skill for Dynamic Agents in Continuous Domains
di: Nieves-Rivera, Delma, et al.
Pubblicazione: (2024)

Automatic MILP Model Construction for Multi-Robot Task Allocation and Scheduling Based on Large Language Models
di: Peng, Mingming, et al.
Pubblicazione: (2025)

Inference-Aware Prompt Optimization for Aligning Black-Box Large Language Models
di: Mahmud, Saaduddin, et al.
Pubblicazione: (2025)

Optimized Agent Shift Scheduling Using Multi-Phase Allocation Approach
di: K, Sanalkumar, et al.
Pubblicazione: (2025)

iScheduler: Reinforcement Learning-Driven Continual Optimization for Large-Scale Resource Investment Problems
di: Hu, Yi-Xiang, et al.
Pubblicazione: (2026)

ScheduleFree+: Scaling Learning-Rate-Free & Schedule-Free Learning to Large Language Models
di: Defazio, Aaron
Pubblicazione: (2026)

Training High-Level Schedulers with Execution-Feedback Reinforcement Learning for Long-Horizon GUI Automation
di: Deng, Zehao, et al.
Pubblicazione: (2025)

A new wave of vehicle insurance fraud fueled by generative AI
di: Hever, Amir, et al.
Pubblicazione: (2025)

Efficient Policy Learning with Hybrid Evaluation-Based Genetic Programming for Uncertain Agile Earth Observation Satellite Scheduling
di: Xue, Junhua, et al.
Pubblicazione: (2026)

CRoCoDiL: Continuous and Robust Conditioned Diffusion for Language
di: Uziel, Roy, et al.
Pubblicazione: (2026)

Distributionally Robust Policy Evaluation and Learning for Continuous Treatment with Observational Data
di: Leung, Cheuk Hang, et al.
Pubblicazione: (2025)

RL$^3$: Boosting Meta Reinforcement Learning via RL inside RL$^2$
di: Bhatia, Abhinav, et al.
Pubblicazione: (2023)

Deep Tabular Research via Continual Experience-Driven Execution
di: Dong, Junnan, et al.
Pubblicazione: (2026)

Bigraph Matching Weighted with Learnt Incentive Function for Multi-Robot Task Allocation
di: Paul, Steve, et al.
Pubblicazione: (2024)

Scalable Ground Station Selection for Large LEO Constellations
di: Kim, Grace Ra, et al.
Pubblicazione: (2025)

Monte Carlo Tree Search Satellite Scheduling Under Cloud Cover Uncertainty
di: Norman, Justin, et al.
Pubblicazione: (2024)

CGEarthEye:A High-Resolution Remote Sensing Vision Foundation Model Based on the Jilin-1 Satellite Constellation
di: Yi, Zhiwei, et al.
Pubblicazione: (2025)

Understanding Persuasion in Long-Running Agents
di: Jeong, Hyejun, et al.
Pubblicazione: (2026)

When Adaptive Rewards Hurt: Causal Probing and the Switching-Stability Dilemma in LLM-Guided LEO Satellite Scheduling
di: Li, Yuanhang
Pubblicazione: (2026)

From Agent Loops to Structured Graphs:A Scheduler-Theoretic Framework for LLM Agent Execution
di: Wei, Hu
Pubblicazione: (2026)

Advancing Algorithmic Approaches to Probabilistic Argumentation under the Constellation Approach
di: Popescu, Andrei, et al.
Pubblicazione: (2024)