Silicon Valley Research and Development Center, Dell Inc.,
Santa Clara, California, USA
Department of Electrical and Computer Engineering, University of Massachusetts,
Dartmouth, Massachusetts, USA
The Genome Institute, Washington University in St. Louis,
St. Louis, USA
Guidelines for Submission
Manuscripts can be submitted until the expiry of the deadline. Submissions must be previously unpublished and may not be under consideration elsewhere.
Papers should be formatted according to the guidelines for authors (see: http://www.sciencepublishinggroup.com/journal/guideforauthors?journalid=135). By submitting your manuscripts to the special issue, you are acknowledging that you accept the rules established for publication of manuscripts, including agreement to pay the Article Processing Charges for the manuscripts. Manuscripts should be submitted electronically through the online manuscript submission system at http://www.sciencepublishinggroup.com/login. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal and will be listed together on the special issue website.
The special issue currently is open for paper submission. Potential authors are humbly requested to submit an electronic copy of their complete manuscript by clicking here.
In recent years, dramatic advances in Artificial Intelligence (AI) have revolutionized the field of AI planning, from theoretical algorithms to the practical applications. This special issue seeks outstanding research on recent advances in AI planning with an emphasis on innovative approaches and technologies as well as their industrial application. Topics of interest include, but are not limited to:
1.Automated planning and scheduling 2.Planning under uncertainty 3.Distributed & multiple agent planning 4.Constraints based planning 5.Constraint Satisfaction Problems (CSP) 6.Planning as satisfiability 7.Planning as constraint satisfaction 8.Planning as model checking 9.Planning on a computational grid, cloud 10.Heuristic search planning 11.Temporal reasoning and scheduling 12.Complexity of planning 13.Case-based planning 14.Markov decision processes 15.Knowledge representation for planning 16.Disaster planning and recovery 17.Case studies