VISTA: An Attention-Based Multi-Agent Reinforcement Learning Architecture for Space Situational Awareness Sensor Tasking

arXiv:2609.23875 · cs.LG, cs.AI, cs.MA, cs.SY, eess.SY · Submitted 2026-09-20 · Read on arXiv

cs.LG, cs.AI, cs.MA, cs.SY, eess.SY

Submitted: 2026-09-20

Updated: 2026-09-20

Comments: 19 pages, 6 figures. Code available at https://github.com/RocketNeurons/VISTA-SSA . Submitted to IEEE TAES

Code: https://github.com/RocketNeurons/VISTA-SSA

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Reinforcement Learning — 24× in this paper · explained in 4 episodes
• Deep Reinforcement Learning — 15× in this paper · explained in 2 episodes
• Action Space — 6× in this paper · explained in 1 episode
• Core — 5× in this paper · explained in 2 episodes
• Generalization — 5× in this paper · explained in 13 episodes
• Accuracy — 4× in this paper · explained in 1 episode
• Advanced Maui Optical and Space Surveillance — 4× in this paper
• Benchmark — 4× in this paper · explained in 2 episodes
• Fidelity — 4× in this paper · explained in 2 episodes
• Adaptation — 3× in this paper · explained in 1 episode
• Information Gain — 3× in this paper · explained in 2 episodes
• Actor — 2× in this paper · explained in 3 episodes
• Cooperation — 2× in this paper · explained in 2 episodes
• Embeddings — 2× in this paper · explained in 2 episodes
• Transformer — 2× in this paper · explained in 2 episodes
• AI Agents — 1× in this paper · explained in 2 episodes
• Ablation — 1× in this paper · explained in 1 episode
• Abstraction — 1× in this paper · explained in 1 episode
• Action Decoder — 1× in this paper · explained in 1 episode
• Adaptability — 1× in this paper · explained in 1 episode
• Attention Mechanism — 1× in this paper · explained in 3 episodes
• Combinatorial Optimization — 1× in this paper · explained in 2 episodes
• Covariance Propagation — 1× in this paper · explained in 2 episodes
• Dec-POMDP — 1× in this paper · explained in 2 episodes
• Deep Reinforcement Learning (DRL) — 1× in this paper · explained in 2 episodes
• Feature Selection — 1× in this paper · explained in 4 episodes
• Latent Space — 1× in this paper · explained in 7 episodes
• Redundancy — 1× in this paper · explained in 2 episodes
• Regularization — 1× in this paper · explained in 3 episodes
• Representation Learning — 1× in this paper · explained in 2 episodes
• Robustness — 1× in this paper · explained in 5 episodes
• Sample Efficiency — 1× in this paper · explained in 4 episodes
• Trace — 1× in this paper · explained in 2 episodes
• VariableEntity Intelligent Sensor Tasking Architecture — 1× in this paper
• Zero-Shot Generalization — 1× in this paper · explained in 5 episodes
• Zero-Shot Transfer — 1× in this paper · explained in 4 episodes

Sources

• Dota 2 with Large Scale Deep Reinforcement Learning
• Proximal Policy Optimization Algorithms
• High-Dimensional Continuous Control Using Generalized Advantage Estimation
• PufferLib: Making Reinforcement Learning Libraries and Environments Play Nice

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