Working Groups: Aims and Scope

TC 12 (ARTIFICIAL INTELLIGENCE) est. 1989, revised 1991

AIMS

Research in AI and promotion of interdisciplinary exchange between AI and other fields of information processing.

SCOPE

1) Further develop the foundation for AI on the basis of computer science principles.

2) Contribute techniques from AI to the enrichment of computer science and information processing.

WG12.1 (KNOWLEDGE REPRESENTATION) est. 1990, revised 1992, 1993

AIMS

- To foster research on the design and implementation of formalisms, methodologies and algorithms for representing and reasoning with knowledge. - To encourage research direction that makes contributions to research in other knowledge-intensive areas of artificial intelligence, such as natural language processing, qualitative reasoning, and high-level vision.

SCOPE

1) The study of models, formalisms, and systems for Knowledge Representation (KR) and of algorithms, proof-theories and methodologies for reasoning therewith. 2) The juxtaposition of a variety of viewpoints from researchers involved in studying KR and those in other areas that rely heavily on represented knowledge (e.g., high-level vision, natural language, and commonsense reasoning). 3) Reconnecting the KR community with traditional KR "consumers" (like natural language understanding, vision and M.L.) and efforts to foster convergence. In particular, the identification of KR issues in these other areas, and of ways KR research could address them.

WG12.2 (MACHINE LEARNING) est 1990, revised 1992

AIM (Not yet defined)

SCOPE

Machine Learning is the automatic or interactive acquisition of knowledge using deductive, inductive or analogical methods. In particular this includes: - the study of machine learning models; - the design of machine learning methods; - the analysis and elaboration of performance criteria for learning programs; - the integration of different learning paradigms.

WG12.3 (REASONING TECHNIQUES) est. 1990, revised 1992

AIMS

To study and develop methods and techniques for knowledge-based inferences and problem solving.

SCOPE

- knowledge-based problem solving and search; - reasoning on ill-defined domains; - metalevel inferences; - cooperative distributed problem solving; - reasoning with incomplete knowledge; - generation of problem representations; - constraint satisfaction; - qualitative reasoning.

WG12.4 (NATURAL LANGUAGE PROCESSING) est. 1990, revised 1992

AIMS

The interactive and integrated study, use, and further development of methods and formalism for representing linguistic and non-linguistic knowledge.

SCOPE

The design and development of computer systems for natural language understanding and generation. It includes parsing, generation, discourse analysis, dialogue handling, machine translation, speech recognition and generation, and theoretical issues in syntax, semantics and pragmatics of natural language.

WG12.5 (KNOWLEDGE-ORIENTED DEVELOPMENT OF APPLICATIONS) est. 1993

AIM (prelim.)

To explore the use of knowledge modelling techniques (knowledge structuring, knowledge acquisition, knowledge explanation) for general applications development.

SCOPE (prelim.)

- conceptual frameworks for application specification and design based on structured knowledge models; - implications on reusability and development of applications by non-programmers; - corporate knowledge management; - relationships with current approaches and life cycles for development and formulation of applications in conventional software engineering and information systems engineering; - new knowledge-based user interfaces for development, explanation and operation of systems supported by this concept of application structure; - standards for knowledge transfer; - integration of AI software and systems with conventional databases, programming languages, and operating systems; - related research issues to support the previous concepts such as knowledge acquisition, learning, validation and implementation techniques.