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CADRe HOME DECISION PATHWAYS ROBUST COGNITIVE DECISION MAKING SOCIAL CONTEXT AND NARRATOLOGY SYSTEM ARCHITECTURE FOR SYSTEMS MODELING

Robust Cognitive Decision Making (RCDMS) Aid mutual learning, problem identification and problem solving for dynamic decision applications. CADRe links with a Modular Abstract Self-Learning Tabu Search (MASTS) MASTS is a general-purpose search engine, based on tabu search, a metaheuristic that relies on memory structures to intelligently navigate the search space of massive complex decision making problems. The application programming interface (API) that defines how MASTS connects to different problems is flexible and abstract, greatly enabling the widest possible variety of applications. MASTS contains a host of default modules, such as Dynamic Neighborhood Selection (DNS) that can be used without modification or can be easily extended to exploit specific problem structures. Modular Abstract Self-Learning Tabu Search (MASTS) Tabu uses an organized framework to evaluate the search space non-exhaustive, but efficient deterministic memory structure may include Recency = tabu tenure Frequency = helps select moves based on event occurrence criteria Memory types can be adaptive/reactive* Intensification Diversification Aspiration, either move or attribute * Learns about solution space as search progresses and adjust accordingly User defines a set of initial conditions Defines an initial neighborhood with a set of “nearby” solutions Finds the best solution within that neighborhood Does not visit any solutions that are off limits Continues this process until set of stopping criteria are met To prevent getting stuck in a local neighborhood TABU also uses: Dynamic neighborhood selection and reactive tabu lists

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[photo: Playa Lake Basin surface, Salar de Atacama, Chile]