Intro3ACI Spring2006

The Applied Computational Intelligence Laboratory: 

The Applied Computational Intelligence Laboratory

Outline: 

Outline Some Applications of the ACI Lab Interactive Distributed Evolutionary Algorithms (IDEAs) Immunity-Based Intrusion Detection Systems Genetic & Evolutionary Protocols Space Systems & Vehicle Optimization Other Applications with Friends Some Tools Developed by the ACI Lab NEVOT and the Design of Distributed ECs X-TOOLSS: eXploration Toolset for Optimization Of Launch and Space Systems

Slide3: 

Some Applications of the ACI Lab

Interactive Distributed Evolutionary Algorithm (IDEA): 

Interactive Distributed Evolutionary Algorithm (IDEA) Researchers Joseph Gay Qin Luo Lacey Montgomery Jonathan Russell Justin Smith Dozier, G., Carnahan, B., Seals, C., Kuntz, L.-A., and Fu, S.-G. (2005). “Collaborative Design Using and Interactive Distributed Evolutionary Algorithm”, The International Journal of Education and Information Technology,  2(1), pp. 21-35, September 2005. Dozier, G., Carnahan, B., Seals, C., Kuntz, L.-A., and Fu, S.-G. (2005). “An Interactive Distributed Evolutionary Algorithm (IDEA) for Design”, Proceedings of 2005 International Conference on Systems, Man, and Cybernetics, pp. October. Luo, Q., Hou, H., and Dozier, G. (2005). “An Interactive Hybrid Swarm Optimization”, Proceedings of HCI International Conference, HCII 2005, CD-ROM.

GENERTIA: Immunity-Based IDS  Design and Re-Design: 

GENERTIA: Immunity-Based IDS Design and Re-Design

Genetic and Evolutionary Protocols: 

Genetic and Evolutionary Protocols

Space Systems & Vehicle Optimization: 

Space Systems & Vehicle Optimization

Some Other Neat Applications: 

Some Other Neat Applications Casey, K., Lim, A., and Dozier, G. (to appear). “Evolving General Regression Neural Networks for Tsunami Detection and Response,” The 2006 Congress on Evolutionary Computation. Imsand, E., Evans, G., Dozier, G. and Hamilton, J. A. (2004). “Using Genetic Algorithms to Aid in a Vulnerability Analysis of National Missile Defense Simulation Software”, Journal of Defense Modeling  Simulation, Volume 1, Issue 4, October 2004, pp. 215-223, The Society for Modeling and Simulation International. Simionescu, A., Beale, D., and Dozier, G. (2006). “Teeth-Number Synthesis of a Multispeed Planetary Transmission Using an Estimation OF Distribution Algorithm”, The Journal of Mechanical Design, January 2006. Yapicioglu, H., Smith, A., and Dozier, G. (to appear). “Solving the Semi-Desirable Facility Location Problem Using Bi-objective Particle Swarm”, The European Journal of Operations Research.

Slide9: 

Some Tools Developed by ACI

X-TOOLSS: 

X-TOOLSS Allows users to optimize any function with a set of evolutionary computations Functions are specified as modules written in any language that is capable of writing and reading text files Modules currently supported: Any executable Java Future module support Perl Matlab Module Selection Window

X-TOOLSS: 

X-TOOLSS EC Selection Window 12 canonical evolutionary computation (EC) algorithms are provided These include genetic algorithms (GAs) particle swarm optimizations (PSOs) differential evolutionary algorithms (DEAs) estimation of distribution algorithms (EDAs) evolutionary programming (EP)

X-TOOLSS: 

X-TOOLSS Results Window Displays the current state of the evolution Generation Best view Current Population view User is capable of specifying the amount of information that is displayed 3 separate logging files are created for long-term storage of the results

Evacuation Design for Lunar Habitation Modules: 

Evacuation Design for Lunar Habitation Modules A is the set of all attractors/exits. O is the set of all obstacles. E is the set of all evacuees. d(p, q) represents the distance between p and q.  is a scaling factor for the attractive forces. It represents the urgency or aggressiveness of the evacuees. Potential Field Model Evacuation Simulation

ACI Website: 

ACI Website http://www.eng.auburn.edu/~gvdozier/ACI