The design productivity gap has been recognized by the semiconductor industry as one of the major threats to the continued growth of system-on-chips and embedded systems. Ad-hoc system-level design methodologies, that lifts modeling to higher levels of abstraction, and the concept of intellectual property (IP), that promotes reuse of existing components, are essential steps to manage design com...

We present a higher-order inference system based on a formal compositional semantics and the wide-coverage CCG parser. We develop an improved method to bridge between the parser and semantic composition. The system is evaluated on the FraCaS test suite. In contrast to the widely held view that higher-order logic is unsuitable for efficient logical inferences, the results show that a system base...

There is a growing recognition that part-whole hierarchies are a very general form of representation, widely used by humans in commonsense reasoning. This paper develops a terminological logic, and related inference mechanisms for representing and reasoning about composite concepts and individuals. A basic terminological logic language is extended with constructs for describing composite concep...

Reactive systems exhibit ongoing, possibly non-terminating, interaction with the environment. Real-time systems are reactive systems that must satisfy quantitative timing constraints. This paper presents a structured compositional design method for discrete real-time systems that can be used to combat the combinatorial explosion of states in the verification of large systems. A composition rule...

Dependency-based Compositional Semantics (DCS) is a framework of natural language semantics with easy-to-process structures as well as strict semantics. In this paper, we equip the DCS framework with logical inference, by defining abstract denotations as an abstraction of the computing process of denotations in original DCS. An inference engine is built to achieve inference on abstract denotati...

Determining the polarity of a sentimentbearing expression requires more than a simple bag-of-words approach. In particular, words or constituents within the expression can interact with each other to yield a particular overall polarity. In this paper, we view such subsentential interactions in light of compositional semantics, and present a novel learningbased approach that incorporates structu...

This paper performs a complexity analysis of a class of serial and parallel compositional models of multiple objects and shows that they enable efficient representation and rapid inference. Compositional models are generative and represent objects in a hierarchically distributed manner in terms of parts and subparts, which are constructed recursively by part-subpart compositions. Parts are repr...

Probabilistic programming is related to a compositional approach to stochastic modeling by switching from discrete to continuous time dynamics. In continuous time, an operator-algebra semantics is available in which processes proceeding in parallel (and possibly interacting) have summed time-evolution operators. From this foundation, algorithms for simulation, inference and model reduction may ...