Larry M. Stephens

Personal ontologies

Corporations can suffer from too much information, and it is often inaccessible, inconsistent, and incomprehensible. The corporate solution entails knowledge management techniques and data warehouses. The paper discusses the use of the personal ontology. The promising approach is an organization scheme based on a model of an office and its information, an ontology, coupled with the proper tools for using it.

Automating supply-chain management

This paper explores a linguistic approach to coordination modeling as a formal basis for supply-chain management (SCM) in manufacturing. The approach promotes the interchange of standard documents: enterprises need only describe their supply processes using OAG business object documents and UML interaction diagrams. Our methodology and tools analyze the documents and interactions in terms of four linguistic primitives and convert the diagrams into specifications and implementations of software agents. The agents then cooperate in automating the resultant supply chain. We evaluate our methodology in the context of several industrial scenarios. We conclude that supply-chain automation using software-agent technology is feasible.

Automating supply chains

A recent study found that supply-chain problems cost companies between 9 and 20 percent of their value over a six-month period (T.J. Becker, 2000). The problems range from part shortages to poorly utilized plant capacity. When you place this in the context of the overall business-to-business (B2B) market expected to reach US

An architecture for control and communications in distributed artificial intelligence systems

7 trillion by 2004 (37 percent of which is projected to be e-commerce sales), it is easy to see that effective supply-chain management (SCM) tools could save companies billions of dollars. Attempts to automate solutions to these problems are complicated by the need for the different companies in a supply chain to maintain the integrity and confidentiality of their information systems and operations. The modeling technologies currently used within the manufacturing business-to-business standards communities, such as the Open Applications Group (http://www.openapplications.org) and RosettaNet (http://www.rosettanet.org) do a good job of capturing user requirements. Unfortunately, current technologies do not explicitly link the requirements to formal process models. This missing link is crucial to efficient SCM implementations.

Constructing Consensus Ontologies for the Semantic Web: A Conceptual Approach

An architecture and implementation for a distributed artificial intelligence (DAI) system are presented, with emphasis given to the control and communication aspects. Problem solving by this system occurs as an iterative refinement of several mechanisms, including problem decomposition, kernel-subproblem solving, and result synthesis. In order for all related nodes to make optimum use of the information obtained from these problem-solving mechanisms, the system dynamically reconfigures itself, thereby improving its performance during operation. This approach offers the possibilities of increased real-time response, improved reliability and flexibility, and lower processing costs. A major component in the node architecture is a database of metaknowledge about the expertise of a nodes own expert systems and those of the other processing nodes. This information is gradually accumulated during problem solving. Each node also has a dynamic-planning ability, which guides the problem-solving process in the most promising direction and a focus-control mechanism, which restricts the size of the explored solution space at the task level while reducing the communication bandwidths required. It also has a question-and-answer mechanism, which handles internode communications. Examples in the domain of digital-logic design are given to demonstrate the operation of the system.

Declarative representations of multiagent systems

Organizational knowledge typically comes from numerous independent sources, each with its own semantics. This paper describes a methodology by which information from large numbers of such sources can be associated, organized, and merged. The hypothesis is that a multiplicity of ontology fragments, representing the semantics of the independent sources, can be related to each other automatically without the use of a global ontology. That is, any pair of ontologies can be related indirectly through a semantic bridge consisting of many other previously unrelated ontologies, even when there is no way to determine a direct relationship between them. The relationships among the ontology fragments indicate the relationships among the sources, enabling the source information to be categorized and organized. An evaluation of the methodology has been conducted by relating numerous small, independently developed ontologies for several domains. A nice feature of the methodology is that common parts of the ontologies reinforce each other, while unique parts are deemphasized. The result is a consensus ontology.

Principles for organizing semantic relations in large knowledge bases

This paper explores the specification and semantics of multiagent problem-solving systems, focusing on the representations that agents have of each other. It provides a declarative representation for such systems. Several procedural solutions to a well-known test-bed problem are considered, and the requirements they impose on different agents are identified. A study of these requirements yields a representational scheme based on temporal logic for specifying the acting, perceiving, communicating, and reasoning abilities of computational agents. A formal semantics is provided for this scheme. The resulting representation is highly declarative, and useful for describing systems of agents solving problems reactively. >

Weaving a computing fabric

Defines principles for organizing semantic relations represented by slots in frame-structured knowledge bases. We organize slots based on the knowledge-level semantics of relations and the symbol-level function of slots that implement the representation language. The symbol-level organization of slots depends on the inferencing and expressive capabilities of the knowledge representation system. At the knowledge level, two entirely different organizational schemes are identified: one based on linguistic similarities and differences, and another based on the types of concepts being related.

Exploiting expertise through knowledge networks

As sources of information relevant to a particular domain proliferate, we need a methodology for locating, aggregating, relating, fusing, reconciling, and presenting information to users. Interoperability thus must occur not only among the information, but also among the different software applications that process it. Given the large number of potential sources and applications, interoperability becomes an extremely large problem for which manual solutions are impractical. A combination of software agents and ontologies can supply the necessary methodology for interoperability.

SWAMI: An autonomous mobile robot for inspection of nuclear waste storage facilities

The paper discusses the necessary capabilities of knowledge networks: categorizing (the ability to classify Web pages and other unstructured data automatically); hyperlinking (the ability to add to each item of information appropriate pointers to other relevant items of information); alerting (the automatic notification of users and agents to new information that might be of interest to them); and profiling (the construction of models of users and agents to describe their interests and expertise).