This paper gives an overview of the development of the field of Knowledge Engineering over the last 15 years. We discuss the paradigm shift from a transfer view to a modeling view and describe two approaches which considerably shaped research in Knowledge Engineering: Role-limiting Methods and Generic Tasks. To illustrate various concepts and methods which evolved in recent years we describe three modeling frameworks: CommonKADS, MIKE and PROTEGE-II. This description is supplemented by discussing some important methodological developments in more detail: specification languages for knowledge-based systems, problem-solving methods and ontologies. We conclude by outlining the relationship of Knowledge Engineering to Software Engineering, Information Integration and Knowledge Management.

/pdf/knowledge-engineering-principles-and-methods-6do1hbj75r.pdf

Knowledge engineering: principles and methods

https://web4.cs.ucl.ac.uk/staff/j.gow/papers/clase05.pdf

Constructing Induction Rules for Deductive Synthesis Proofs

Since emotions are expressed through a combination of verbal and non-verbal channels, a joint analysis of speech and gestures is required to understand expressive human communication. To facilitate such investigations, this paper describes a new corpus named the “interactive emotional dyadic motion capture database” (IEMOCAP), collected by the Speech Analysis and Interpretation Laboratory (SAIL) at the University of Southern California (USC). This database was recorded from ten actors in dyadic sessions with markers on the face, head, and hands, which provide detailed information about their facial expressions and hand movements during scripted and spontaneous spoken communication scenarios. The actors performed selected emotional scripts and also improvised hypothetical scenarios designed to elicit specific types of emotions (happiness, anger, sadness, frustration and neutral state). The corpus contains approximately 12 h of data. The detailed motion capture information, the interactive setting to elicit authentic emotions, and the size of the database make this corpus a valuable addition to the existing databases in the community for the study and modeling of multimodal and expressive human communication.

/pdf/iemocap-interactive-emotional-dyadic-motion-capture-database-2ffyt1sb5i.pdf

IEMOCAP: interactive emotional dyadic motion capture database

This book arises from a series of workshops on collaborative learning, that gathered together 20 scholars from the disciplines of psychology, education and computer science. The series was part of a research program entitled 'Learning in Humans and Machines' (LHM), launched by Peter Reimann and Hans Spada, and funded by the European Science Foundation. This program aimed to develop a multidisciplinary dialogue on learning, involving mainly scholars from cognitive psychology, educational science, and artificial intelligence (including machine learning). During the preparation of the program, Agnes Blaye, Claire O'Malley, Michael Baker and I developed a theme on collaborative learning. When the program officially began, 12 members were selected to work on this theme and formed the so-called 'task force 5'. I became the coordinator of the group. This group organised two workshops, in Sitges (Spain, 1994) and Aix-en-Provence (France, 1995). In 1996, the group was enriched with new members to reach its final size. Around 20 members met in the subsequent workshops, at Samoens (France, 1996), Houthalen (Belgium, 1996) and Mannheim (Germany, 1997). Several individuals joined the group for some time but have not written a chapter. I would nevertheless like to acknowledge their contributions to our activities: George Bilchev, Stevan Harnad, Calle Jansson and Claire O'Malley.

/pdf/what-do-you-mean-by-collaborative-learning-4yh17cjr7v.pdf

What do you mean by collaborative learning

This article presents Gaia: a methodology for agent-oriented analysis and design. The Gaia methodology is both general, in that it is applicable to a wide range of multi-agent systems, and comprehensive, in that it deals with both the macro-level (societal) and the micro-level (agent) aspects of systems. Gaia is founded on the view of a multi-agent system as a computational organisation consisting of various interacting roles. We illustrate Gaia through a case study (an agent-based business process management system).

/pdf/the-gaia-methodology-for-agent-oriented-analysis-and-design-wgk16eqrby.pdf

The Gaia Methodology for Agent-Oriented Analysis and Design

LNAI was established in the mid-1980s as a topical subseries of LNCS focusing on artificial intelligence. This subseries is devoted to the publication of state-of-the-art research results in artificial intelligence, at a high level and in both printed and electronic versions making use of the well-established LNCS publication machinery. As with the LNCS mother series, proceedings and postproceedings are at the core of LNAI; however, all other sublines are available for LNAI as well. The topics in LNAI include automated reasoning, automated programming, algorithms, knowledge representation, agent-based systems, intelligent systems, expert systems, machine learning, natural-language processing, machine vision, robotics, search systems, knowledge discovery, data mining, and related programming languages.

Lecture Notes in Artificial Intelligence

In this paper we present the overall vision and the high level requirements of the digital infrastructure which is going to be built in three of the sport facilities which will host part of the Winter Olympic Games Milano-Cortina 2026, and another winter sports professional facility for sking. Not only the infrastructure will enable the performance analysis of athletes, but also it will contribute to the sustainability of the investment for the Games and will provide opportunities of development for the territory and new qualified jobs for local people.

A cloud-based management system for a data infrastructure in four winter sport facilities

Distance learning during pandemic: was it really so bad?

When building a new application we are increasingly confronted with the need of reusing and integrating pre-existing knowledge. Nevertheless, it is a fact that this prior knowledge is virtually impossible to reuse as-is. This is true also in domains, e.g., eHealth, where a lot of effort has been put into developing high-quality standards and reference ontologies, e.g. FHIR1. In this paper, we propose an integrated methodology, called iTelos, which enables data and knowledge reuse towards the construction of Interoperable Electronic Health Records (iEHR). The key intuition is that the data level and the schema level of an application should be developed independently, thus allowing for maximum flexibility in the reuse of the prior knowledge, but under the overall guidance of the needs to be satisfied, formalized as competence queries. This intuition is implemented by codifying all the requirements, including those concerning reuse, as part of a purpose defined a priori, which is then used to drive a middle-out development process where the application schema and data are continuously aligned. The proposed methodology is validated through its application to a large-scale case study.

P. Bouquet

Papers

Lecture Notes in Artificial Intelligence

A cloud-based management system for a data infrastructure in four winter sport facilities

Distance learning during pandemic: was it really so bad?

Building Interoperable Electronic Health Records as Purpose-Driven Knowledge Graphs