Haskell’s popularity has driven the need for ever more expressive type system features, most of which threaten the decidability and practicality of Damas-Milner type inference. One such feature is the ability to write functions with higher-rank types – that is, functions that take polymorphic functions as their arguments. Complete type inference is known to be undecidable for higher-rank (impre...

This article describes an object-oriented inference engine for PROLOG. The inference engine is part of the Graphically Oriented Development Environment for Logic (Gödel) programming. Gödel incrementally translates source clauses to a persistent clause base in which each clause is an object. The inference engine is a distributed one in which each clause object knows how to unify and execute itse...

Understanding and using the data and knowledge encoded in semantic web documents requires an inference engine. F-OWL is an inference engine for the semantic web language OWL language based on F-logic, an approach to defining kame-based systems in logic. F-OWL is implemented using XSB and Flora-2 and takes full advantage of their features. We describe how F-OWL computes ontology entailment and c...

This paper presents an application of Point-Interval logic (PIL) for the problem of planning timesensitive aspects of a mission. The logic incorporates both point and interval structures of time associated with mission activities and also provides for qualitative and quantitative descriptions of temporal requirements among mission activities. An algorithm is presented that extends the inference...

Understanding and using the data and knowledge encoded in semantic web documents requires an inference engine. F-OWL is an inference engine for the semantic web language OWL language based on F-logic, an approach to defining kame-based systems in logic. F-OWL is implemented using XSB and Flora-2 and takes full advantage of their features. We describe how F-OWL computes ontology entailment and c...

Support for modularity allows complex ontologies to be separated into smaller pieces (modules) that are easier to maintain and compute. Instead of considering the entire complex ontology, users may bene t more by starting from a problem-speci c set of concepts (signature of problem) from the ontology and exploring its surrounding logical modules. Additionally, an ontology modularization mechani...

The core of our resource analysis for the embedded systems language Hume is a resource-generic, type-based inference engine that employs the concept of amortised costs to statically infer resource bounds. In this paper we present extensions and improvements of this resource analysis in several ways. We develop and assess a call count analysis for higher-order programs, as a specific instance of...

It is considered that a key to overcoming the limitations of classical artificial intelligence is to process distributed representations of information without symbolizing them. However, conventional neural networks require local or symbolic representations to perform complicated processing. Here we present a brain-like inference engine consisting of a nonmonotone neural network that makes infe...

The presented control scheme utilizes Adaptive Neuro Fuzzy Inference System (ANFIS) controller to track a reference engine rotational speed and disturbance rejection during engine idling. To evaluate the performance of the controller a model of the engine is simulated and simulation results presented. ANFIS implements a first order Sugeno-style fuzzy system. It is a method for tuning an existin...

The discovery of dependencies between components of a network can reveal relationships among components of multi-tier applications and the underlying IT infrastructure, such as servers and databases. Knowledge of these dependencies is thus important for the management of large distributed, heterogeneous and virtualized systems, where it is difficult to maintain an accurate view of how network a...