Executive Description:

  FSS is a scientific research project that aims at developing a novel search algorithm inspired on fish-schools. The algorithm is intelligent, that is, it is able to learn by its own functioning and self-regulate (i) direction of the search effort as well as (ii) the search granularity. Fish-school algorithms devised in this project produce a very interesting balance between exploration and exploitation abilities, both, highly desirable in a search tool.

 Objectives:

1. Which features from fish-schools are useful for search algorithms;

2. What are appropriate application domains for FSS;

3. What are the single and mutual importance of each parameter within FSS;

4. How FSS can be customized for real-world problems;

5. Which new features can be added onto FSS to increase its functionality.

 Key-words:  Fish-school search, Search algorithms, Computational Intelligence.

 Period: March/2007 until December/2012.

 Laboratory:

1. CIRG - Escola Politécnica de Pernambuco - Universidade de Pernambuco.

 Preliminary thoughts:

1. Search problems can be hard to be performed, hence they can be resource consuming;

2. Certain search problems can be of high dimensionality;

3. Most search problems have no structured environment;

4. Nature has evolved many complex systems that are able to tackle the above mentioned difficulties.

 Expected results:

1. Inteligent and self-regulated approach to search problems;

2. Search tool to operate in unstructured and high-dimensional environments;

3. Cheap and fast computations;

4. Easily customizable interface;

5. Expandable core across many application domains.

 Other Information, visit the Official Website of FSS:

              Website of FSS