11th Annual Symposium on Combinatorial Search
https://sites.google.com/view/socs18/
IMPORTANT DATES
* Abstract submission: April 29, 2018
* Paper submission: May 1, 2018
* Notification: June 1, 2018
* Symposium: July 14-15, 2018
SUBMISSIONS
Submissions have to be made via EasyChair.
All submissions must be formatted in AAAI Style.
Accepted papers will be included in the SoCS proceedings.
We welcome the following kinds of submissions:
* Original Papers (Long or Short)
Original papers are technical papers that report on substantial research or position papers discussing ideas and concepts related to search. Long papers may be up to 8 pages in length, plus an additional page for references only. Short papers may be up to 4 pages, plus an additional page for references only. Long and short original papers should be new work which has not been published in (nor is currently simultaneously under review at) any other archival publication venue.
* Previously Published Papers
In order to foster the exchange of ideas at SoCS, we encourage authors to submit extended abstracts of papers describing new research which has been published in other venues in the last year. These abstracts may be up to 2 pages, plus an additional page for references only. The abstract should reference the original paper.
TOPICS OF INTEREST
Topics of interest include but are not limited to the following:
* Analysis of search algorithms
* Automated synthesis of lower bounds
* Automatic algorithm selection and parameter tuning
* Bounding and pruning techniques
* Combinatorial puzzles
* Continuous problem solving
* External-memory and parallel search
* Incremental and active learning in search
* Meta-reasoning and search
* Methodology and critiques of current practice
* Model-based search
* Random versus systematic search strategy selection
* Portfolios of search algorithms
* Real-time search
* Search in goal-directed problem solving
* Search space discretization for continuous state-space problems
* Self-configuring and self-tuning algorithms
* Symmetry handling
* Time, memory, and solution quality trade-offs
* Search in big data
* Constraint search
* Search in robotics
* Search-based diagnosis
* Real-life applications
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