Reinforcement Learning-Guided Evolutionary Policy Optimization for Preference-Adjustable Heterogeneous Agile Earth Observation Satellite Scheduling

arXiv:2608.24470 · cs.AI · Submitted 2026-08-25 · Read on arXiv

cs.AI

Submitted: 2026-08-25

Updated: 2026-08-25

Terminology

Actor — 26× in this paper · explained in 3 episodes
Reinforcement Learning — 10× in this paper · explained in 4 episodes
Evolutionary Policy Optimization — 9× in this paper
Action Space — 7× in this paper · explained in 1 episode
Resource Constraints — 5× in this paper · explained in 3 episodes
Adaptive Large Neighborhood Search — 3× in this paper
Reward Function — 3× in this paper · explained in 2 episodes
Action Decoder — 2× in this paper · explained in 1 episode
Combinatorial Optimization — 2× in this paper · explained in 2 episodes
Consistency — 2× in this paper · explained in 3 episodes
Grey Wolf Optimizer — 2× in this paper
Robustness — 2× in this paper · explained in 5 episodes
Adaptability — 1× in this paper · explained in 1 episode
Adaptation — 1× in this paper · explained in 1 episode
Adaptive Exploration State-Space Particle Swarm Optimization — 1× in this paper
Benchmark — 1× in this paper · explained in 2 episodes
Core — 1× in this paper · explained in 2 episodes
Decode — 1× in this paper · explained in 2 episodes
Interpretability — 1× in this paper · explained in 15 episodes
Markov Decision Process (MDP) — 1× in this paper · explained in 11 episodes
Objective Function — 1× in this paper · explained in 2 episodes
Q-learning — 1× in this paper · explained in 3 episodes
Reinforcement Learning (RL) — 1× in this paper · explained in 25 episodes

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