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[Savannah-register-public] [task #8915] Submission of sayphi

From: Tomas de la Rosa
Subject: [Savannah-register-public] [task #8915] Submission of sayphi
Date: Thu, 11 Dec 2008 17:08:04 +0000
User-agent: Mozilla/5.0 (X11; U; Linux i686; es-ES; rv: Gecko/2008092510 Ubuntu/8.04 (hardy) Firefox/3.0.3


                 Summary: Submission of sayphi
                 Project: Savannah Administration
            Submitted by: tomdelarosa
            Submitted on: Thu Dec 11 17:08:03 2008
         Should Start On: Thu Dec 11 00:00:00 2008
   Should be Finished on: Sun Dec 21 00:00:00 2008
                Category: Project Approval
                Priority: 5 - Normal
                  Status: None
                 Privacy: Public
        Percent Complete: 0%
             Assigned to: None
             Open/Closed: Open
         Discussion Lock: Any
                  Effort: 0.00



A new project has been registered at Savannah 
This project account will remain inactive until a site admin approves or
discards the registration.

= Registration Administration =

While this item will be useful to track the registration process, *approving
or discarding the registration must be done using the specific Group
<> page*,
accessible only to site administrators, effectively *logged as site
administrators* (superuser):

* Group Administration

= Registration Details =

* Name: *sayphi*
* System Name:  *sayphi*
* Type: Official GNU software
* License: GNU General Public License v2 or later


==== Description: ====
SAYPHI is planning and learning architecture for heuristic planning research
purpose. It includes a forward state-space heuristic planner like FF planner.
It has a set
of search algorithms that could be used with the pluggable heuristic of the
system. SAYPHI, also includes two include two learning systems to improve the
planner performance.  CABALA is a Case-based Reasoner that learns abstracted
state transitions in order to guide algorithms with a domain-dependent learned
knowledge. ROLLER is learning system that acquires knowledge in form o
relational decision trees. These trees are generalized policies that could be
used within the search to speed-up
the learning process.

==== Tarball URL: ====


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