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Multi-agent autonomous reasoning systems have emerged as a promising planning technique for addressing satellite defense problems. The main challenge is to extend and scale up the capabilities of current and emerging reasoning and planning methods to handle the characteristics of the satellite defense problem. This paper focuses on some key critical research issues that need to be addressed in order to perform automated planning and execution fitted to the specific nature of response to ASAT attacks, and provides MAARS, a new autonomous reasoning framework for satellite defense. As the core of MAARS, we present MODERN, a new execution-centric method for DEC-POMDPs explicitly motivated by model uncertainty. There are two key innovative features in MODERN: (i) it maintains an exponentially smaller model of other agents’ beliefs and actions than in previous work and then further reduces the computation-time and space expense of this model via bounded pruning; and (ii) it reduces execution-time computation by exploiting BDI theories of teamwork, and limits communication reasoning to key trigger points. We demonstrate a proof of concept of MAARS in the simplified ASAT mitigation scenario. We then show initial evaluation results of MAARS in ASAT domains that are critical in advancing the state-of-the-art in providing autonomous reasoning to delve into unperceived models as well as deal with exponential explosion of the computational complexity of current algorithms. |
