TC 12 - Artificial Intelligence - Aims and Scopes

est. 1989, revised 1991, 2004

AIMS

*    To foster the development and understanding of Artificial Intelligence and its applications worldwide.

*    To promote interdisciplinary exchanges between Artificial Intelligence and other fields of information processing.

*    To contribute to the overall aims and objectives and further development of IFIP as the international body for Information Processing. 

SCOPE

Artificial Intelligence covers a wide range of techniques, which can be applied to a very wide range of application areas. Its subfields include (but are not restricted to) the following:

*    Automated Reasoning                                    

*    Belief Revision

*    Case-Based Reasoning

*    Computer Vision

*    Constraint Satisfaction

*    Data Mining

*    Evolutionary Algorithms

*    Intelligent Agents

*    Intelligent Planning and Scheduling

*    Intelligent Robotics

*    Knowledge Acquisition

*    Knowledge Discovery and Data Mining

*    Knowledge Engineering

*    Knowledge-Based Systems

*    Knowledge Management

*    Knowledge Representation and Reasoning

*    Machine Learning

*    Machine Translation

*    Model-based Reasoning

*    Natural Language Processing

*    Neural Nets

*    Pattern Recognition

*    Qualitative Reasoning

*    Search

*    Semantic Web

*    Temporal Reasoning


WG12.1 - Knowledge Representation and Reasoning
est. 2004

AIM

To study and develop theory and techniques for knowledge representation and reasoning.


SCOPE

The scope of the Working Group's activities includes (but is not restricted to) the following:

*    Abductive Reasoning

*    Inductive Reasoning

*    Non-monotonic Reasoning

*    Reasoning about Actions and Change

*    Spatial Reasoning

*    Temporal Reasoning

*    Automated Reasoning

*    Computational Logic

*    Logic Programming

*    Situation Calculus

*    Production Systems

*    Semantic Networks

*    Frames

*    Object-orientated Representation

*    Bayesian Networks

 


WG12.2 - Machine Learning and Data Mining
est. 2003, revised 2005

AIM

To explore computer methodology and algorithms that improve automatically through experience. Applications range from data mining programs that discover general rules in large data sets, to information filtering systems that automatically learn users' interests. 

SCOPE
 

*    Concept Learning and Inductive Learning

*    Association Rules

*    Case-based Learning

*    Artificial Neural Networks

*    Bayesian Learning

*    Uncertainty Learning

*    Reinforcement Learning

*    Evolutionary Learning

*    Perceptual Learning

*    Computational Learning Theory

*    Population-based Learning

*    Data Mining

*    Application Case Study


WG12.3 - Intelligent Agents
est. 2003

AIM

To study and develop theory and techniques for intelligent agents. 

SCOPE

*    Theory and agent modeling

*    Agent architectures

*    Agent-based software engineering

*    Coordinating, cooperation and negotiation

*    Evolution, adaptation and learning

*    Multiple agents

*    Mobile agents

*    Agent-based grid computing

*    Agent-based applications


WG12.4 - (joint with WG2.12, see TC2)


WG12.5 - Artificial Intelligence Applications
est. 1993, rev. 2003

AIM

To explore the use of Artificial Intelligence techniques for applications development.  

SCOPE

All areas of application in which Artificial Intelligence techniques can give benefits to users.

Techniques for application development including:

*    Conceptual frameworks for application specification and design

*    User interface design

*    Integration of AI software and systems with conventional databases, programming languages, and operating systems

*    Related research issues such as knowledge acquisition, learning, validation and implementation techniques. 


WG12.6 - Knowledge Management
est. 1993, revised 2003, 2008

AIMS

*    To develop advanced methods for organizing, accessing and exploiting multidisciplinary knowledge within organizations and enterprises.

*    To bring together various areas of KM research and technology to meet this challenge, e.g. knowledge transfer and modeling, optimisation, natural language understanding, speech and image processing and understanding, reasoning methods, learning methods, communication methods, social aspects, complex problem solving, decision support, human-machine interaction, serious games.

*    To develop technology for intelligent support of Knowledge Cultivators, e.g. intelligent knowledge navigation systems, multi modal interface, automatic translation, competency management, e- and m-activities such as learning, collaborative research and design, business, process control.

*    To share worldwide experience in the above domains.

SCOPE

Methodology, technologies, processes, and systems for supporting all aspects of knowledge management as communication, collaboration, learning, innovation, decision making, investigation, embedding and archiving.

Knowledge thinking.

Knowledge Holonomy – the interplay between individual, organizational, enterprise and society levels. Cross organisational.

Technology trends include:

*    Intelligent multimodal knowledge acquisition and retrieval

*    Knowledge discovery   

*    Technology for sustainable development

*    Convergence of intelligences

*    Technology for Knowledge Innovation

*    Human machine interaction and collaboration

*    Virtual reality and Games for KM


WG12.7 - Computer Vision
est. 2003 – dissolved 2008