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Found 6 papers, 0 papers with code
A Systems-Theoretical Formalization of Closed Systems
There is a lack of formalism for some key foundational concepts in systems engineering.
Active Learning with Combinatorial Coverage
The proposed methods are data-centric, as opposed to model-centric, and through our experiments we show that the inclusion of coverage in active learning leads to sampling data that tends to be the best in transferring to better performing models and has a competitive sampling bias compared to benchmark methods.
Exposing Surveillance Detection Routes via Reinforcement Learning, Attack Graphs, and Cyber Terrain
Reinforcement learning (RL) operating on attack graphs leveraging cyber terrain principles are used to develop reward and state associated with determination of surveillance detection routes (SDR).
Core and Periphery as Closed-System Precepts for Engineering General Intelligence
Engineering methods are centered around traditional notions of decomposition and recomposition that rely on partitioning the inputs and outputs of components to allow for component-level properties to hold after their composition.
Discovering Exfiltration Paths Using Reinforcement Learning with Attack Graphs
Reinforcement learning (RL), in conjunction with attack graphs and cyber terrain, are used to develop reward and state associated with determination of optimal paths for exfiltration of data in enterprise networks.
Real Time Strategy Language
General RTS agents are AI gaming systems that can play any RTS games, defined in the RTS language.
