posted by user: herrmann || 10872 views || tracked by 33 users: [display]

ICAPS 2014 : 24th International Conference on Automated Planning and Scheduling

FacebookTwitterLinkedInGoogle


Conference Series : International Conference on Automated Planning and Scheduling
 
Link: http://icaps14.icaps-conference.org
 
When Jun 21, 2014 - Jun 26, 2014
Where Portsmouth, NH, USA
Abstract Registration Due Oct 29, 2013
Submission Deadline Nov 5, 2013
Notification Due Dec 20, 2013
Categories    artificial intelligence   planning   scheduling
 

Call For Papers

The 2014 edition of the International Conference on Automated Planning and Scheduling will take place June 21-26 in Portsmouth, NH, USA.

ICAPS 2014 is part of the ICAPS conference series. ICAPS is the premier forum for exchanging news and research results on theory and applications of intelligent planning and scheduling technology.

The conference features a pre-conference program of workshops and tutorials on current research topics. The main technical program consists of invited talks by leading scientists working in the area, presentations of technical papers, as well as system demonstrations. For graduate students, the pre-conference program includes a Doctoral Consortium.

Related Resources

ICAPS 2022   The 32nd International Conference on Automated Planning and Scheduling
ICDM 2022   22nd IEEE International Conference on Data Mining
RDDPS 2022   ICAPS'22 Workshop on Reliable Data-Driven Planning and Scheduling
CFMAI 2022   2022 4th International Conference on Frontiers of Mathematics and Artificial Intelligence (CFMAI 2022)
HPlan 2022   ICAPS Hierarchical Planning Workshop
FAIML 2022   2022 International Conference on Frontiers of Artificial Intelligence and Machine Learning (FAIML 2022)
ASE 2022   37th IEEE/ACM International Conference on Automated Software Engineering
ICMLA 2022   IEEE International conference on Machine Learning and Applications
EMSOFT 2022   International Conference on Embedded Software
IDEAL 2022   23rd International Conference on Intelligent Data Engineering and Automated Learning