PDS (Process Diagnosis System) is an expert system shell developed in the early 1980's. It could handle thousands of sensor inputs and produce thousands of diagnostic messages with confidence factors based on complex logic designed to mimic the thinking of human experts. PDS went into commercial operation in 1985 to monitor seven power plant generators from a centralized diagnostic center at Westinghouse Power Generation headquarters. In the 1990’s the popularity of advanced technology gas turbines provided a renaissance in PDS utilization. The software has undergone rewrites and improvements since its inception, and the current PCPDS now supports the Siemens Power Diagnostics® Center with centralized rule based monitoring of over 1200 gas turbines, steam turbines, and generators.

Organizations need to accurately understand the skills and competencies of their human resources in order to effectively respond to internal and external demands for expertise and make informed hiring decisions. In recent years, however, human resources have become highly mobile, making it more difficult for organizations to accurately learn their competencies. In such environment, organizations need to rely significantly on third parties to provide them with useful information about individuals. These sources and the information they provide, however, vary in degrees of trust and validity. In a previous paper, we developed an ontology for skills and competencies and modeled and analyzed the various sources of information used to derive the belief in an individual's level of competency. In this paper, we present an approach based on social network analysis for identifying unreliable sources of competency information. We explore the conditions under which evaluations given by an individual or a group about another can be trusted. We evaluate this approach using recommendation data gathered by crawling user profiles in LinkedIn.

High volume, B2C eCommerce web sites that often experience millions of visitors and 100,000s of orders a day in the lead up to major gift giving occasions, must meet customer demands of high availability, responsiveness, and functionality. These same web sites often integrate a large number of 3rd party web services that need to but often fail to meet the same demands. This paper describes a Semantic Web-based solution to meeting such demands. By distinguishing between action versus information, required versus optional, time constrained, and substitutable services, combined with the semantic web concepts of information validity, provenance and trust, more targeted and flexible responses to service failures can be provided.

To stay competitive within the market, organizations need to understand the skills and competencies of their human resources in order to best utilize them. This paper focuses on the problem of modeling human resources in a dynamic environment, and presents a formal ontology for representing, inferring, and validating skills and competencies over time.

This article introduces a measurement ontology for applications to Semantic Web applications, specifically for emerging domains such as microarray analysis. The Semantic Web is the next generation Web of structured data that are automatically shared by software agents, which apply definitions and constraints organized in ontologies to correctly process data from disparate sources. One facet needed to develop Semantic Web ontologies of emerging domains is creating ontologies of concepts that are common to these domains. These general “common-sense” ontologies can be used as building blocks to develop more domain-specific ontologies. However most measurement ontologies concentrate on representing units of measurement and quantities, and not on other measurement concepts such as sampling, mean values, and evaluations of quality based on measurements. In this article, we elaborate on a measurement ontology that represents all these concepts. We present the generality of the ontology, and describe how it is developed, used for analysis and validated.

This paper formalizes the semantics of trust and studies the transitivity of trust. On the Web, people and software agents have to interact with "strangers". This makes trust a crucial factor on the Web. Basically trust is established in interaction between two entities and any one entity only has a finite number of direct trust relationships. However, activities on the Web require entities to interact with other unfamiliar or unknown entities. As a promising remedy to this problem, social networks-based trust, in which A trusts B, B trusts C, so A indirectly trusts C, is receiving considerable attention. A necessary condition for trust propagation in social networks is that trust needs to be transitive. However, is trust transitive? What types of trust are transitive and why? There are no theories and models found so far to answer these questions in a formal manner. Most models either directly assume trust transitive or do not give a formal discussion of why trust is transitive. To fill this gap, this paper constructs a logical theory of trust in the form of ontology that gives formal and explicit specification for the semantics of trust. Based on this formal semantics, two types of trust -- trust in belief and trust in performance are identified, the transitivity of trust in belief is formally proved, and the conditions for trust propagation are derived. These results give theoretical evidence to support making trust judgment using social networks on the Web.

The agent view provides a level of abstraction at which we envisage computational systems carrying out cooperative work by interoperating globally across networks connecting people, organizations and machines. A major challenge in building such systems is coordinating the behavior of the individual agents to achieve the individual and shared goals of the participants. As part of a larger project targeted at developing an Agent Building Shell for multiagent applications, we have designed and implemented a coordination language aimed at explicitly representing, applying and capturing coordination knowledge for multiagent systems. The language provides KQML-based communication, an agent definition and execution environment, support for modeling interactions as multiple structured conversations among agents, rule-based approaches to conversation selection and execution, as well as an interactive tool for in context acquisition and debugging of cooperation knowledge. The paper presents these components in detail and then shows how the coordination language is used in the Agent Building Shell to manage content-based information distribution scenarios among agents and the coordination aspects of conflict management processes that occur when agents encounter inconsistencies. The major application of the system is the construction and integration of multiagent supply chain systems for manufacturing enterprises. This application is used throughout the paper to illustrate the introduced concepts and language constructs.

A model of decentralized problem solving, called distributed constrained heuristic search (DCHS), that provides both structure and focus in individual agent search spaces to optimize decisions in the global space, is presented. The model achieves this by integrating decentralized constraint satisfaction and heuristic search. It is a formalism suitable for describing a large set of distributed artificial intelligence problems. The notion of textures that allow agents to operate in an asynchronous concurrent manner is introduced. The use of textures coupled with distributed asynchronous backjumping, a type of distributed dependency-directed backtracking that the authors have developed, enables agents to instantiate variables in such a way as to substantially reduce backtracking. The approach has been tested experimentally in the domain of decentralized job-shop scheduling. A formulation of distributed job-shop scheduling as a DCHS and experimental results are presented.>

Representation of activity knowledge is important to any application which must reason about activities such as new product management, factory scheduling, robot control, vehicle control, software engineering, and air traffic control. This paper provides an integration of the underlying theories needed for modeling activities. Using the domain of large computer design projects as an example, the semantics of activity modeling is described. While the past research in knowledge representation has discovered most of the underlying concepts, our attempt is toward their integration. This includes the epistemological concepts for erecting the required knowledge structure; the concepts of activity, state, goal, and manifestation for the adequate description of the plan and the progress; and the concepts of time and causality to infer the progression among the activities. We also address the issues which arise due to the integration of aggregation, time, and causality among activities and states.

The relationship between organization theory and distributed systems is studied. By viewing distributed systems as analogous to human organizations, concepts and theories germane to the management science field of organization theory can be applied. Task complexity, uncertainty, coupled with resource constraints are shown to be important factors in deciding how a system is to be distributed.