The introduction of the concept of state novelty has advanced the state of the art in deterministic online planning in Atari-like problems and in planning with rewards in general, when rewards are defined on states. In classical planning, however, the success of novelty as the dichotomy between novel and non-novel states was somewhat limited. Until very recently, novelty-based methods were not able to successfully compete with state-of-the-art heuristic search based planners. In this work we adapt the concept of novelty to heuristic search planning, defining the novelty of a state with respect to its heuristic estimate. We extend the dichotomy between novel and non-novel states and quantify the novelty degree of state facts. We then show a variety of heuristics based on the concept of novelty and exploit the recently introduced best-first width search for satisficing classical planning. Finally,we empirically show the resulting planners to significantly improve the state of the art in satisficing planning.
Today almost every IT specialist uses models of some form or another. Models help raise the abstraction level of a system description. Although models usually describe IT systems statically, they can also be used to describe the dynamic behaviour of the system. The OMG's MDA ® approach suggests describing business and application logic separately from any underlying platform technology in Platform Independent Models. The UML 2.0 provides powerful and flexible behavioural modelling capabilities.As the focus of the development process shifts from being code-centric to model-centric, the need for an environment to debug and execute models becomes more apparent. The ability to execute models provides additional avenues for the exploitation of the models in validation, verification, and simulation. The use of executable models enables the visualization and discovery of defects early in the development cycle, avoiding costly rework at later stages.We describe an architecture for implementing a generic model execution engine that enables the simulation of models. The main advantages of our architecture are its generic nature and its dedication to maintaining controllability and observability of the simulation. We have used this generic framework to build a UML simulator, which can be extended to support different UML profiles. The architecture also supports non-UML models.
Cyclic dependencies among software components are considered an architectural problem that increases the development time and prevents proper reuse. One cause for the existence of such dependencies is the improper organization of elements into components.Optimal reorganization of the components that resolves the cyclic dependencies in large and complex software systems is extremely difficult to perform manually and is not computationally feasible to perform automatically.We present an approach for automatic untangling of cyclic dependencies among components for cycles of any size, having direct or transitive dependencies on one another. Our approach aims at minimizing the modifications to the original structure of the system, while taking into account various architectural properties.We evaluate our solution on twelve open source and three industrial applications. We demonstrate its applicability and value through architectural metrics and feedback from system architects.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.