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The Department of Computer Science hosts the world-famous computer scientist and inventor of Genetic Algorithms (GA's), Dr. Genalytics Model 6.0 transforms large amounts of transaction data into predictive intelligence and uses genetic algorithms to automatically search and identify key combinations of time series variables found in any dataset.
Starting today, past and present IlliGAL lab members and affiliates will team up to blog on genetic algorithms, evolutionary computation, and related subjects.
GECCO, I was re-reading Sam Mahfoud's paper titled "population sizing for Sharing methods". Since niching mechanism is one of the key components of hierarchical and multiobjective genetic algorithms, the population-sizing paper deserves renewed attention.
Over a number of years, I've followed research in iGAs and some time ago, I started to collect information about market research and product development with the idea of founding a company to do just that using interactive GA technology. Scalable Parallel Random Number Generators Library (SPRNG): An RNG library that combines various available random number generators and supports both serial and parallel platforms. Mersenne Twister (MT): An RNG which has a period of 2^19937-1 with an assured 623-dimensional equidistribution property (Thanks to Jaume for pointing me to MT).
Experiments showed that a lower mixing rate increases both the population size needed and the convergence time. Business Week article gives an overview of BBN's Boomerang project now fielded in Iraq to protect Allied troops by detecting and locating sniper fire. This story is fine as far as it goes, but as GA afficianadoes well know, the BBN effort was supported by a crack team of card-carrying genetic algorithmists. This year's Genetic and Evolutionary Computation Conference (GECCO-2005) is 25-29 June 2005 in Washington DC. Those with artistic or creative talent should try their skills at designing the new SIGEVO logo as the competition ends February 7th. Martin Pelikan's book titled "Hierarchical Bayesian Optimization Algorithm: Toward a New Generation of Evolutionary Algorithms" is now available.
More details regarding hBOA and to download the software visit the hBOA page and Martin's webpage.
Lately, I have moved from WEKA to D2K, a data mining framework developed by the Automated Learning Group at the National Center for Supercomputing Applications.
We all know that computational complexity of GAs depends primarily on the population size and the number of generations.
What I like on using the bisection method is that all parameter tweaking will be done automatically (and thus I don't have to do it myself), because the remaining GA parameters do not influence time complexity as much (mostly by some constant factor and that's not so important when we talk about asymptotic upper bounds).
Of course, the above thinking is correct only if larger populations lead to better solutions (given enough generations we should all be able to believe this fact) and if smaller populations do not significantly increase the number of generations (in all cases I studied, any sufficiently large population size lead to about the same number of generations, as can be expected for many variants of evolutionary algorithms based primarily on recombination). Technology Review article also highlights the history of evolutionary computation a€“ briefly mentioning the work of Holland, Goldberg, Koza, and others. Theory and Applications of Efficient Multi-Objective Evolutionary Algorithms (CS, Feng Chia University, 2004) was ranked number one among all CS dissertations in a national competition held under the auspices of the Institute of Information & Computing Machinery (IICM). Oregon Daily Emerald reports that James Bean, noted operations researcher, genetic algorithmist, and inventor of the random keys technique for permutation and other combinatorial problems, is using genetic algorithms to help develop sustainable automobile technology in his new role as Dean of the Lundquist College of Business.
The usage of EDAs can help addressing two major issues in XCS: (1) knowledge extraction and (2) structure identification.
Toronto Globe and Mail reports that researchers at Laurentian University are using genetic algorithms to schedule mining of ore deposits.
Science Daily posts a University of Michigan press release entitled Falling Prey to Machines?
According to Holland, the problem with developing artificial intelligence through things like genetic algorithms is that researchers don't yet understand how to define what computer programs should be evolving toward.
According to Holland, advances in software have not kept pace with the exponential improvements in hardware processing power, and there are many artificial intelligence problems that cannot be solved by simply performing more calculations. Acovea (analysis of compiler options via evolutionary algorithm) is an open source project which utilizes GAs to tune the optimization flags for GCC to yield the fastest code specifically for your computer.
Another reason for the current situation is that human lifespans are no longer a good match to the turnover in intellectual ideas. So, it is in this sense, that the acceptance of SIGEVO by ACM couldn't come at a better time, and should be seen as a very positive thing. Of course, department heads when asked about tenure and promotion will tell you that each case is special and is scrutinized without regard for brand names.
It will take some time to know the overall effect, and indeed, joining a large bureaucratic organization like ACM will come with its share of constraints and costs. Sam Williams's recent article "Unnatural Selection" in Technology Review is getting some blog traction. Another script I use very often is a perl wrapper for gnuplot, the plotting program from the GNU project. This script receives as parameters a variable-length number of data files to overlap in the same plot. Don't forget, the new motherboards and processors drain a lot of power, so you need about 1.5 Amps per node. ATA Engineering announced the release of version 1.0 of the Attune package for test-analysis correlation and model updating. In beta testing, a key aerospace customer used Attune to carry out hundreds of real-time correlation iterations during modal testing of a launch vehicle payload, whereas prior to this they were limited to less than a dozen manual correlations a week.
Additional information is available from the Attune product website or the full press release. Finally, a third way of approaching animation synthesis was presented by Torsten Reil, from Natural Motion. However, by abstracting the proposed optimizations on large but abstracted code with a proprietary representation, and then projecting execution time based on resource utilization and resulting code classifications for fitness, their system was able to find speedups in a just a couple of hours with only a 2% drop in speedup from that work using actual execution times. John Holland's course, Introduction to Adaptive Systems, wondering what all the genetics stuff had to do with adaptive systems. That experience on my thesis left me with a thirst to better understand genetic algorithms, how they work, and how to make them work better. My 2002 book, The Design of Innovation, tells the long version of this story, but the basic idea of little modeling is to construct models for various effects in isolation (selection alone, crossover alone, mutation alone), and use dimensional analysis to create models for complex phenomena from pairs of simpler models.
More recently, Ali Yassine, Tian-Li Yu, and I have carried the little modeling approach over to organizational theory here. Or, are you already a model looking to get your career jump started and find new modeling agencies and modeling markets?
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GeoHub is a portal of open location-based data from city departments that empowers both the public and city employees to explore, analyze and build on the data. Youths are highly enthusiastic about starting their own businesses in order to realize their dreams. Hundreds of runners and walkers gathered in the afternoon of November 8, 2015 at Ap Lei Chau for the 12th CyberRun for the Rehabilitation with the theme of “Sunset Jogging to Cyberport”. Esri China (HK) participated in the 20th Anniversary Ceremony of our long-term business partner NetCraft Information Technology (Macau) Co.
Esri User Conference (Esri UC) 2015 was once again successfully held in San Diego from July 18-24.
In Esri User Conference every year, Esri presents hundreds of organizations worldwide with Special Achievement in GIS (SAG) Awards.


GIS professionals, users and friends who open the website of Esri China (Hong Kong) every day may have a pleasant surprise in early August.
Smart City promises to enhance the quality of city living by using Information and Communication Technology and related initiatives are generating interests among different sectors in the city. The revamped Statutory Planning Portal 2 (SPP2) of Town Planning Board launched last fall has quickly become one of the most popular website providing public information.
The 7.8 magnitude earthquake occurred in Nepal on 25 Apr 2015 has taken over 8,000 lives and injured over 19,000 people. Esri is supporting organizations that are responding to earthquake disasters with software, data, imagery, project services, and technical support.
The Hong Kong Council of Social Service in 2002, the Caring Company Scheme aims at cultivating good corporate citizenship.
The Esri Asia Pacific User Conference (APUC) has finally returned to Hong Kong after a decade and the 10th Esri APUC was successfully held in 27-28th January 2015.
This year, about 600 delegates from 20 countries of Asia, Oceania, Europe and North America descended upon the Hong Kong Convention and Exhibition Centre.
By studying time series patterns, organizations can identify credit risks, anticipate customer attrition, and detect probable bankruptcies. In April 1994, a graduate student named Kate Sherwood (Ducky) put up the first IlliGAL web page. In the last American election cycle, blogging grew as a force to rival the mainstream media. The population-sizing estimate though derived for fitness sharing, also holds for other niching methods such as restricted tournament selection as well. Ever since Dawkins famous Blind Watchmaker code, and Caldwell and Johnston's Faceprints work at ICGA 91, the idea of having user-driven subjective functions in place of predetermined objective functions has opened the door to evolving art, music, poetry, and more.
My dreams of a great startup were dashed one semester when during my genetic algorithms course, some students researching their class project uncovered a company that was already vigorously pursuing interactive GAs in marketing applications.
A simple idea such as a round robin of small disjoint training sets greatly helps Pittsburgh classifier systems in the quest for generality. Not only is the math difficult, but the system also had to work in the cacophony of urban warfare, including echoes from shots -- and do it on the move.
An article written by BBNers Hussain, Montana, Brinn & Cerys entitled Genetic algorithms for UGV navigation, sniper fire localization, and unit of action fuel distribution was presented last June at GECCO 2004 at the Workshop on Military and Security Applications of Evolutionary Computation (MSAEC-2004).
In his book, Martin presents a principled method for designing and analyzing scalable genetic algorithms that can solve boundedly-difficult, hierarchically-decomposable problems in polynomial (usually sub-quadratic) time.
I know Martin and Jaume have also been using some of this tools too in their data mining related papers. LIBSVM is an integrated software for support vector classification, (C-SVC, nu-SVC ), regression (epsilon-SVR, nu-SVR) and distribution estimation (one-class SVM ). Given that we know the optimum, the number of generations can be determined by the GA itself---when the GA finds the optimum or the entire population converges to it (or gets close enough), we've got it.
The basic idea is to first determine a reasonable initial interval (min,max) of population sizes where min is too small and max is too large. To eliminate noise, the bisection can be run several times and the results of all bisection runs can be averaged (right now I use 10 rounds of bisection, each with 10 runs). To determine whether or not the second condition is at least partially satisfied, one can try one problem size (rather larger than smaller) and test whether the overall complexity decreases for larger populations than the one determined by the bisection.
From jet engine fan blade design to minimizing power consumption of long-distance pipelines, the article cites several applications of genetic algorithms and genetic programming. Recently, such approaches are slowly infiltrating in the learning classifier systems world. Knowledge extraction addresses the issue of mining problem knowledge from the final solution developed by XCS. He told me that the problematic GA runs would converge to a mediocre solutions, but different parts within those solution were of good quality. Thesis Symmetry in the Representation of an Optimization Problem and related papers, available as IlliGAL technical reports 2001020 and 2001030 are a good starting point for anyone interested in knowing more about symmetry and synchronization problems in optimization in general, and GAs in particular. While hardware performance continues to double almost every year and a half, the doubling time for software performance is at least 20 years.
I've been heavily involved in the process of this transformation, and so my views are not entirely unbiased (no one's views are entirely unbiased or so any good postmodernist would claim), but I think this move is good for ISGEC, good for ACM, good for the field of genetic and evolutionary computation, and good for computer science. First wave evolutionary computation researchers (and cyberneticists of all stripes) in the late 50s and 60s were just getting their sea legs under them when Minsky and Papert's premature and misleading hatchet job on neural networks appeared and took the wind out of cybernetic sails generally. With GECCO as an ACM conference proceedings, young faculty can safely put their work there without endlessly defending their choice. Department heads have told me that the decision to move from ISGEC to SIGEVO will make absolutely no difference to them.
But, in the end, I believe the young people in the PhD pipeline will benefit immensely through higher probability of hiring, better chances to tenure, and improved prospects of funding as the once outlaw field of genetic algorithms and evolutionary computation comes in off the range, hangs up its six-shooter, and becomes a law-abiding denizen of the mainstream of computer science.
I have used it extensively to compute statistical tests, and I made a script to automatize most of the testing process. It uses the Bonferroni correction to ajust the significance level of the tests for the multiple comparisons.
The script generates draft plots just to check how do the results look, without the overhead of launching other programs that can generate more fancy plots like Matlab. We mostly use the cluster to run multiple GA runs to collect statistics, and also for testing the effect of different parameters on the scalability of the algorithms (For example, see Martin's blog). That means they produce a lot of heat, but nothing that a few well placed fans and couple of ACs can't fix. He tackled the problem by using a set of controllers and running it through a set of genetic algorithms to develop the motion he wanted out of them. This still gave an overall 10-20% speedup when the found choice of optimizations were applied. Shortly thereafter, I proposed applying genetic algorithms to gas pipeline optimization and rule learning, did so, and went on to take my first teaching job at the University of Alabama.
And that thirst led me to try difference equations, Markov chains, transform methods, anything that I could get my hands on, to help me do a better job in GA analysis and design.
For example, we might create a model for convergence time under selection alone, combine this with a model for mixing under crossover alone, and consider the pairwise effect as a dimensionless ratio of the two times. Simple to use, attractive and cost-effective, shopping carts are becoming one of the primary ways that your customers can buy your goods & services online! His talk on Complex Adaptive Systems (CAS) will discuss the study of complexity, innovation, and relations between CAS and GA's.
To my discredit, I didn't understand why she was so fascinated by the web, but in my defense, I didn't get in her way.
In less well followed topics, blogging is growing at astonishing rates, and we hope that IlliGAL Blogging will become a resource and focal point for intelligent discourse in the growing community of genetic and evolutionary computation (GEC). Of course, a lot of water has passed over the iGA dam since the early days, and for those interested in a fairly recent update on the state of interactive evolutionary computation, I recommend Hideyuki Takagi's article.
That company, Affinova, has married iGAs and practical market research and product development notions to create a unique line of products and services. On the Michigan approach, however, such issue was settled down after the idea of evolving classifiers based on accuracy by Wilson (now celebrating the 10th anniversary of its publication). The paper details the development of Boomerang and other GA-based military-security applications. Written in Java, it is easy to use, providing a flexible environment for rapid preliminary filtering and analysis of raw data.
The thing I like the most about D2K, and one of the reasons for switching, is the data flow oriented paradigm that it uses.
It is a GNU project which is similar to the S language and environment which was developed at Bell Laboratories (formerly AT&T, now Lucent Technologies) by John Chambers and colleagues.
Most likely, the complexity increases with the population size and thus the bisection can run the experiments for us.


Chen takes the methodology of The Design of Innovation and applies it to understanding the approximate complexity of multiobjective evolutionary algorithms (MOEAs). The goal is to identify most important features in the problem and the dependencies among those features. I remembered Clarissa's worka€”that she did during her visit to IlliGALa€”about how strong symmteries in problems such as Ising and other spin-glass models can cause synchorinization problems and how niching methods can be used to avoid them.
Intelligence was just one of many traits that human beings exploited to increase their odds of survival, and the test for survival was absolute. For too long, GAs and EC more generally have lived in the backwaters of academic and industrial life. When he was asked how the acceptance of his revolutionary ideas in quantum physics was going, it is reported that he said, "Wonderful, lots of funerals." In Plank's day, perhaps the natural turnover in faculty matched the turnover of ideas, but in our time, rapid change in thinking has not been matched with a concomitant shortening of faculty life expectancy. With ACM affiliated journals in EC and GP, department heads have the moral equivalent of a Good Housekeeping seal of approval on our field to rely upon instead of the pleas of a lone faculty member up for tenure. But consumers will tell you that their decisions to buy products are also made on a case-by-case basis without regard for brands--as their grocery baskets fill with Crest, Tide, Mach 3, Ragu, Pepsi, Twinkies, and Tide. It supposes that the results are paired, like the results obtained, for instance, from a stratified ten-fold cross-validation test. Since then, quite a few people have asked me a how to build such a cluster, what components to buy, etc. Although I had succeeded in applying GAs in my problem domain, my doing so left me with as many questions as I answered. At first, my studies took me toward more esoteric and sophisticated tools, but then my training in fluid mechanics kicked (somewhere between my leaving Alabama and coming to Illinois), and I turned to the methodology of little models, including facetwise models, and patchquilt integration using dimensional analysis. This approach, though algebraically simple, is remarkably powerful in helping sort out experimental results and organize a researcher's thinking.
Since then, the IlliGAL web site has grown and users from countries around the world generate some 8.4 million hits in nearly 200,000 visits annually. Subsequently I met company executive Rob Frasca in another context, and got the chance to tell him how Affinova was the company that broke my entrepreneurial heart.
Like supersonic airplanes, bullets create shock waves -- mini-sonic booms -- as they speed through the air.
These efforts are the result of longstanding GA work at BBN initiated by Dave Davis (now of NuTech Solutions) and carried on by Dave Montana and other hardworking GA types. Recently, I have notice the existence at least more than 20 different projects using such framework. Using an intuitive graphical editor, complicated analysis and visualization task are rapidly deployed by simple drag & drop. I have been using it in some of my recent research, and if you are interested in such areas, I definitely recommend you to take a look at it.
A "good" population size should be the one that ensures reliable convergence to the optimum (where "reliable may be defined any way we want, for instance, that the algorithm finds the optimum successfully in 9 out of 10 independent runs). Thereafter, he successfully applies carefully designed MOEAs to problems in production planning and design of nearest-neighbor classifiers.
Bean was on the faculty of the Department of Industrial and Operations Engineering (IOE) of the University of Michigan for many years, where he also held the position of Associate Dean for Academic Affairs. The extracted knowledge may not only be used for further data mining, but may actually be re-fed into the system giving it further competence in solving problems in which dependent features, that is, building blocks, need to be processed effectively.
So, I suggested him that there might be synchronization issues with the problematic instances and using a niching method might be the solution. No mention is made of who the reseachers are or what department, college, or lab they come from. Defining an equivalent test of fitness for targeting intelligence as an evolutionary goal for machines, however, has been elusive. Finally, the rise of symbolic AI and the subsequent cybernetics winter made it academically disreputable to persist in the "folly" of genetic algorithms and evolutionary computation, but persist the field did, and we are here today because of the courage of a small group who swam against the intellectual currents of the 60s, 70s, and 80s.
The result is large numbers of powerful faculty in charge with ideas in mind that are more than a little behind the time. In a busy world, trusted brands allow buyers to get quality products at low risk of error and low search costs. These optimizations seek to reduce memory or power usage, or to speedup the needed execution time. And although I had used GAs to help solve interesting engineering problems, I was unhappy with GAs--and my own lack of understanding of GAs--as engineered objects. The website has undergone kaizen or continual improvement since Ducky's early efforts, and this blog represents the latest in a series of new features to be added to the site over the years. For those interested in a nice case study of marrying GAs and business read the Affinova white paper here. So if engineers arrange seven microphones like the spines of a sea urchin, a shock wave from a bullet will hit each microphone at a slightly different time, like a wave lapping against different pebbles on a beach.
It is difficult enough working in the obscure vineyards of GAs and EC, but when a group used to toiling in obscurity does something deserving of national recognition, it would be nice if the mainstream business press would get the story right and at least mention the names of the people who really got the job done. I have been heavily using D2K in the DISCUS project, and I have no regrets about not using WEKA anymore. Herb Simon talks about decomposability of most complex real-world systems, which is a feature that a good evolutionary algorithm should be able to exploit. The dissertation concludes with novel theory and empirical work that carry over the method of fitness inheritance to MOEAs.
Lo and behold, he came back yesterday and said using niching significantly improved the GA performance!
Nonetheless, a Google search on the search terms, "genetic algorithms," "mining," and "Laurentian University" quickly leads to the following link.
Thus, it is difficult to draw comparisons between how human intelligence developed and how artificial intelligence could evolve. After all, evolution is one of the biggest ideas in all of science, and the impact of modern genetics is hard to overstate, so it seems quite natural that computations based on evolution and genetics should have an important place in science and technology. Unfortunately, the most obvious solutions to this problem are serious felonies, and no one is here suggesting that steps be taken to cull the herd. In the new world of ACM and SIGEVO, CS departments and their heads will be able to rely on a trusted brand in one of the most important decisions they make, the hiring, retention, and promotion of faculty.
Her system tries to determine which combinations and orderings of optimizations should be performed on which portions of the code. Only good words is what I have about D2K's quality and how much effort the ALG people put into it to make a great package easy to extend and customize. I'd strongly suggest this book to anyone interested in somewhat a philosphical discussion of what types of problems we should be trying to solve with our optimizers.
The Laurentian University Mining Automation Laboratory (LUMAL) under the direction of Nick Vayenas is applying simulation, robotics, and genetic algorithms to various mining problems. Why, then, have GAmists and ECers been largely relegated to second tier schools, non-tenured posts, or non-CS departments (even, god forbid, engineering departments)? And thanks to Srikant-Uni-of-Glasgow-Travails and SoloGen for the links to IlliGAL Blogging. We can pray for crisper reporting from the the Globe and Mail, but in the meanwhile, odds are that this is the GA mining work that was so cryptically cited. Work in this area traditionally relies on actual execution time for fitness, which may require up to 50 hours to determine which optimizations should be performed on a small piece of code.



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