Kit-Ying Hui

KRAFT: knowledge fusion from distributed databases and knowledge bases

The KRAFT project aims to investigate how a distributed architecture can support the transformation and reuse of a particular class of knowledge, namely constraints, and to fuse this knowledge so as to gain added value, by using it for constraint solving or data retrieval.

Experience in Using RDF in Agent-Mediated Knowledge Architectures

We report on experience with using RDF to provide a rich content language for use with FIPA agent toolkits, and on RDFS as a metadata language. We emphasise their utility for programmers working in agent applications and their value in Agent-Oriented Software Engineering. Agent applications covered include Intelligent Information Agents, and agents forming Virtual Organisations. We believe our experience vindicates more direct use of RDF, including use of RDF triples, in programming knowledge architectures for a variety of applications.

Developing Finite Domain Constraints - A Data Model Approach

We describe a technique for formulating a problem for solution by a finite domain constraint solver, where the finite domains can be modelled in correspondence with an Entity-Relationship diagram or UML Class diagram. This works particularly well where data for the problem is retrieved from database(s) over a network, but we believe the modelling discipline will be more generally useful. We show how relationships are conveniently represented using the infers operator of the generalised constraint propagation (Propia) library of ECLiPSe. Further, we can then express sets of quantified constraints over the data model in the declarative Colan language, and use this to generate equivalent ECLiPSe code directly. The user then has only to maintain the declarative version of the constraints, which are much easier to read. They can also be reused in many ways by fusing them with constraints from other sources, as in the KRAFT project. An important subclass of such constraints behave as conditional constraints which need delayed application, and we discuss experience in making such constraints more active in the solving process.

Constraints as Mobile Specifications in E-Commerce Applications

We show how quantified constraints expressed in a sub-language of first-order logic, against a shared data model that is free to evolve, provide an excellent way of transporting domain-specific semantics along with the data. In this form it can be processed automatically by various intelligent components, instead of requiring human intervention. It can also be combined with other constraints, by algebraic transformation against a common data model, and then passed to an appropriate solver. These techniques have been tested in a classic e-business application scenario: configuring a product from parts selected from e-vendors’ catalogues, whilst conforming to requirements specific to the parts, expressed as mobile constraints.

A Hybrid Approach to Distributed Constraint Satisfaction

We present a hybrid approach to Distributed Constraint Satisfaction which combines incomplete, fast, penalty-based local search with complete, slower systematic search. Thus, we propose the hybrid algorithm PenDHyb where the distributed local search algorithm DisPeL is run for a very small amount of time in order to learn about the difficult areas of the problem from the penalty counts imposed during its problem-solving. This knowledge is then used to guide the systematic search algorithm SynCBJ. Extensive empirical results in several problem classes indicate that PenDHyb is effective for large problems.

Supporting Collaboration Through Semantic-Based Workflow and Constraint Solving

This paper describes our efforts to provide a collaborative problem solving architecture driven by semantic-based workflow orchestration and constraint problem solving. These technologies are based on shared ontologies that allows two systems of very different natures to communicate, perform specialised tasks and achieve common goals. We give an account of our approach for the workflow assisted collaboration with constraint solving capabilities. We found that systems built with semantic (web) based technologies is useful for collaboration and flexible to enhance the system with specialised capabilities. However, much care must be exercised before correct semantics may be exchanged and collaborations occur smoothly.

Multi-Hyb: A Hybrid Algorithm for Solving DisCSPs with Complex Local Problems

A coarse-grained Distributed Constraint Satisfaction Problem (DisCSP) is a constraint problem where several agents, each responsible for solving one part (a complex local problem), cooperate to determine an overall solution. Thus, agents solve the overall problem by finding a solution to their complex local problem which is compatible with the solutions proposed by other agents for their own local problems. Several approaches to solving DisCSPs have been devised and can be classified as systematic search and local search techniques. We present Multi-Hyb, a two-phase hybrid algorithm for solving coarse-grained DisCSPs which uses both systematic and local search during problem solving. Phase 1 generates key partial solutions to the global problem using systematic search. Concurrently, a penalty-based local search algorithm attempts to find a global solution to the problem using these partial solutions. If a global solution is not found in phase 1, the information learnt from phase 1 is used to inform the search carried out during the next phase. Phase two runs a systematic search algorithm on complex variables guided by the following knowledge obtained in phase 1: (i) partial solutions and; (ii) complex local problems which appear more difficult to satisfy. Experimental evaluation demonstrates that Multi-Hyb is competitive in several problem classes in terms of: (i) the communication cost and (ii) the computational effort needed.

Acquisition and maintenance of constraints in engineering design

The Designers Workbench is a system, developed by the Advanced Knowledge Technologies (AKT) consortium to support designers in large organizations, such as Rolls- Royce, by making sure that a design is consistent with the specification for the particular design as well as with the companys design rule book(s). Currently, to capture the constraint information, a domain expert (design engineer) has to work with a knowledge engineer to identify the constraints, and it is then the task of the knowledge engineer to encode these into the Workbenchs knowledge base (KB). This is an error prone and time consuming task. It is highly desirable to relieve the knowledge engineer of this task, and so we have developed a tool, ConEditor, that enables domain experts themselves to capture and maintain these constraints. The tool allows the user to combine selected entities from the domain ontology with keywords and operators of a constraint language to form a constraint expression. We hypothesize that to apply constraints appropriately, it is necessary to understand the context in which each constraint is applicable. We refer to this as application conditions. We plan to make these application conditions machine interpretable and investigate how they, together with a domain ontology, can be used to support the verification and maintenance of constraints.

Designing for scalability in a knowledge fusion system

The knowledge reuse and fusion/transformation (KRAFT) project has defined a generic agent-based architecture to support knowledge fusion — the process of locating and extracting knowledge from multiple, heterogeneous on-line sources, and transforming it so that the union of the knowledge can be applied in problem-solving. KRAFT focuses on knowledge in the form of constraints expressed against an object data model defined by a shared ontology. KRAFT employs three kinds of agent: facilitators locate appropriate on-line sources of knowledge; wrappers transform heterogeneous knowledge to a homogeneous constraint interchange format; mediators fuse the constraints together with associated data to form a dynamically-composed constraint satisfaction problem, which is then passed to an existing constraint solver engine to compute solutions. n nThe KRAFT architecture has been designed to be scalable to large numbers of agents; this paper describes the features of the architecture designed to support scalability. In particular, we examine static techniques that underpin the growth of large-scale KRAFT networks, and dynamic techniques that allow reorganisation of a KRAFT network as it increases in scale.

Constraint and Data Fusion in a Distributed Information System

Constraints are commonly used to maintain data integrity and consistency in databases. This ability to store constraint knowledge, however, can also be viewed as an attachment of instructions on how a data object should be used. In other words, data objects are annotated with declarative knowledge which can be transformed and processed.