AIEDAM: Artificial Intelligence for Engineering
Design, Analysis and Manufacturing is a journal intended to
reach two audiences: engineers and designers who see
AI technologies as powerful means for solving difficult
engineering problems; and researchers in AI and Computer
Science who are interested in applications of AI and in
the theoretical issues that arise from such applications.
The journal publishes significant, original articles about AI theory
and applications based on the most up-to-date research in all branches
and phases of engineering. Suitable broad topic areas include:
analysis and evaluation; selection; configuration and design;
manufacturing and assembly; and concurrent engineering.
Specific subareas include: cognitive modeling; creativity; learning;
qualitative reasoning; spatial reasoning; graphics and modeling;
constraints and preferences; style and brands; human-computer
interaction; multi-modal interaction; computational linguistics;
design and process planning; scheduling; simulation; optimization;
distributed teams and systems; multi-agent applications; design
rationale and histories; functional, behavioral and structural
reasoning; knowledge management; and ontologies.
AIEDAM is also interested in original,
major applications of state-of-the-art AI techniques to
important engineering problems (termed "practicum papers").
In addition to the rapid publication and dissemination of unsolicited
research papers, AIEDAM is committed to
producing special issues on important, timely topics.
One key purpose of AIEDAM is to provide the
community with a forum for publishing high quality papers that can be
cited as the basis for future work, and to provide support to this
community through publication, high quality reviewing, and special
issues.
Please read AIEDAM's
Policy
Statement about papers that concern Neural Nets, Evolutionary
techniques, or other powerful, general-purpose techniques.
AIEDAM is indexed in Compendex Plus,
SciSearch, Research Alert, and CompuMath Citation Index.
