TC 12 - Artifical
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 modelling
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, rev. 2003
AIMS
To develop advanced methods for organizing, accessing and
exploiting heterogeneous multimedia data which becomes available through modern
communication technology
To bring together various areas of AI research and technology to
meet this challenge, e.g. knowledge representation, natural language
understanding, speech and image understanding, reasoning methods, learning, and
agent technologies
To develop technology for diverse applications, e.g.
subject-specific brokers, corporate knowledge bases, data-mining tools,
content-based query languages, multimedia data indexing schemes and web-based
information services.
SCOPE
Technologies, processes, and systems for supporting such aspects
of knowledge management as collaboration, learning, innovation, decision
making, investigation, embedding and archiving.
The interplay between inter-organizational, enterprise,
group-based, and personal technologies.
Technology
trends including
the convergences of E-Learning with Knowledge Management,
E-Business with Knowledge Management, Collaborative Commerce with Knowledge
Management, and Science of Learning with Knowledge Management
the gradual alignment of business process management tools in
enterprise portals
the impacts of peer-to-peer and grid computing on enterprise
collaborations and computing.
WG12.7
- Computer Vision
est. 2003 – dissolved 2008