MIT AI Lab: B. Williams, H. Shrobe, R. Laddaga Dynamic Domain Architectures for Model Based Autonomy New Ideas Controller Plant mode identification control s’(t) (t) f s (t) g o(t) Model Goals Model-based Deductive Executive Executable Models with Explicit Constraints Multiple domain specific languages for physical constituents and software components Embedded in common base language, deductive framework Integration of models via fast runtime deductive constraint resolution Runtime compilation and optimization Models preserved for diagnosis in case of breakdown Three key services all model-driven: Mode identification (diagnosis) Reactive planning Resource management Impact Schedule Toolkit for embedded SW framework developers helps to capture & structure knowledge of the application domain. Embedded frameworks can be integrated with each other. Application programmers can implement and evolve application functionality at a high level, in concise, domain-appropriate, terms. Application users obtain: more functionality in a more timely fashion; they can rely on the correctness and performance of the application as it continues to evolve. Reactive Executive for Model-Based Autonomy milestones: 1: design of next-gen Livingstone; 2: implementation of next-gen Livingstone; 3: testing and evaluation of next-generation reactive executive. Developers' Toolkit for Model-Based Autonomy milestones: 1: design meta-language describing DDA programs; 2: prototype DDA-based Application Generator; 3: test, evaluate DDA toolkit Integration, Experimentation and Evaluation milestones: 1: prototype testbed application; 2: Application specific toolkits for testbed; 3:Reactive Executive for Model-Based Autonomy MIT AI Lab: B. Williams, H. Shrobe, R. Laddaga