The Knowledge Level Approach To Intelligent Information System Design

Traditional approaches to building intelligent information systems employ an ontology to define a representational structure for the data and information of interest within the target domain of the system. At runtime, the ontology provides a constrained template for the creation of the individual objects and relationships that together define the state of the system at a given point in time. The ontology also provides a vocabulary for expressing domain knowledge typically in the form of rules (declarative knowledge) or methods (procedural knowledge). The system utilizes the encoded knowledge, often in conjunction user input, to progress the state of the system towards the specific goals indicated by the users. While this approach has been very successful, it has some drawbacks. Regardless of the implementation paradigm the knowledge is essentially buried in the code and therefore inaccessible to most domain experts. The knowledge also tends to be very domain specific and is not extensible at runtime. This paper describes a variation on the traditional approach that employs an explicit knowledge level within the ontology to mitigate the identified drawbacks

Service discovery and composition : PreDiCtS approach

The proliferation of Web Services is fostering the need for service-discovery and composition tools to provide more personalisation during the service retrieval process. In this paper, we describe the motivating details behind PreDiCtS, a framework for personalised service-retrieval. In our approach we consider that similar service composition problems can be tackled in a similar manner by reusing and adapting past composition best practices or templates. The proposed retrieval process uses a mixed- initiative technique based on Conversational Case-Based Reasoning (CCBR), that provides i) for a clearer identification of the user’s service requirements and ii) based on these requirements, finds suitable service templates that satisfy the user’s goal. We discuss how retrieval can vary through the use of different CCBR algorithms and how adaptation can be performed over the retrieved templates thus providing the personalisation feature in PreDiCtS.peer-reviewe

Proceedings of the 2004 ONR Decision-Support Workshop Series: Interoperability

In August of 1998 the Collaborative Agent Design Research Center (CADRC) of the California Polytechnic State University in San Luis Obispo (Cal Poly), approached Dr. Phillip Abraham of the Office of Naval Research (ONR) with the proposal for an annual workshop focusing on emerging concepts in decision-support systems for military applications. The proposal was considered timely by the ONR Logistics Program Office for at least two reasons. First, rapid advances in information systems technology over the past decade had produced distributed collaborative computer-assistance capabilities with profound potential for providing meaningful support to military decision makers. Indeed, some systems based on these new capabilities such as the Integrated Marine Multi-Agent Command and Control System (IMMACCS) and the Integrated Computerized Deployment System (ICODES) had already reached the field-testing and final product stages, respectively. Second, over the past two decades the US Navy and Marine Corps had been increasingly challenged by missions demanding the rapid deployment of forces into hostile or devastate dterritories with minimum or non-existent indigenous support capabilities. Under these conditions Marine Corps forces had to rely mostly, if not entirely, on sea-based support and sustainment operations. Particularly today, operational strategies such as Operational Maneuver From The Sea (OMFTS) and Sea To Objective Maneuver (STOM) are very much in need of intelligent, near real-time and adaptive decision-support tools to assist military commanders and their staff under conditions of rapid change and overwhelming data loads. In the light of these developments the Logistics Program Office of ONR considered it timely to provide an annual forum for the interchange of ideas, needs and concepts that would address the decision-support requirements and opportunities in combined Navy and Marine Corps sea-based warfare and humanitarian relief operations. The first ONR Workshop was held April 20-22, 1999 at the Embassy Suites Hotel in San Luis Obispo, California. It focused on advances in technology with particular emphasis on an emerging family of powerful computer-based tools, and concluded that the most able members of this family of tools appear to be computer-based agents that are capable of communicating within a virtual environment of the real world. From 2001 onward the venue of the Workshop moved from the West Coast to Washington, and in 2003 the sponsorship was taken over by ONR’s Littoral Combat/Power Projection (FNC) Program Office (Program Manager: Mr. Barry Blumenthal). Themes and keynote speakers of past Workshops have included: 1999: ‘Collaborative Decision Making Tools’ Vadm Jerry Tuttle (USN Ret.); LtGen Paul Van Riper (USMC Ret.);Radm Leland Kollmorgen (USN Ret.); and, Dr. Gary Klein (KleinAssociates) 2000: ‘The Human-Computer Partnership in Decision-Support’ Dr. Ronald DeMarco (Associate Technical Director, ONR); Radm CharlesMunns; Col Robert Schmidle; and, Col Ray Cole (USMC Ret.) 2001: ‘Continuing the Revolution in Military Affairs’ Mr. Andrew Marshall (Director, Office of Net Assessment, OSD); and,Radm Jay M. Cohen (Chief of Naval Research, ONR) 2002: ‘Transformation ... ’ Vadm Jerry Tuttle (USN Ret.); and, Steve Cooper (CIO, Office ofHomeland Security) 2003: ‘Developing the New Infostructure’ Richard P. Lee (Assistant Deputy Under Secretary, OSD); and, MichaelO’Neil (Boeing) 2004: ‘Interoperability’ MajGen Bradley M. Lott (USMC), Deputy Commanding General, Marine Corps Combat Development Command; Donald Diggs, Director, C2 Policy, OASD (NII

Taxonomic conversational case-based reasoning

Abstract. Conversational Case-Based Reasoning (CCBR) systems engage a user in a series of questions and answers to retrieve cases that solve his/her current problem. Help-desk and interactive troubleshooting systems are among the most popular implementations of the CCBR methodology. As in traditional CBR systems, features in a CCBR system can be expressed at varying levels of abstraction. In this paper, we identify the sources of abstraction and argue that they are uncontrollable in applications typically targeted by CCBR systems. We contend that ignoring abstraction in CCBR can cause representational inconsistencies, adversely affect retrieval and conversation performance, and lead to case indexing and maintenance problems. We propose an integrated methodology called Taxonomic CCBR that uses feature taxonomies for handling abstraction to correct these problems. We describe the benefits and limitations of our approach and examine issues for future research.