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Computational Neuroscience and Compartmental Modeling
Published in Bahman Zohuri, Patrick J. McDaniel, Electrical Brain Stimulation for the Treatment of Neurological Disorders, 2019
Bahman Zohuri, Patrick J. McDaniel
The implications of this intelligence for society would be far-reaching—in some cases, very destructive. The political structure might fall apart if we knew we were no longer the smartest species on Earth if we were overshadowed by the intelligence of galactic proportions. A superintelligence might view humans as we do insects—and we all know what humans do to bugs when they overstep their boundaries! This year, many renowned scientists, academics, and CEOs, including Stephen Hawking and Elon Musk, signed a letter, which was presented at the International Joint Conference on Artificial Intelligence. The letter warns about the coming dangers of artificial intelligence, urging that we should be prudent as we venture into the unknowns of an alien intelligence.18
Artificial Intelligence Challenged by Uncertainty
Published in Deyi Li, Yi Du, Artificial Intelligence with Uncertainty, 2017
With the extensive use of databases and networks, people are immersed in massive data, but are still thirsty for the knowledge and data they actually need. Data authenticity and security have become a major concern. However, people’s quest for particular knowledge has made it possible for data mining to rise quickly in the field of knowledge engineering. The term data mining made its first appearance in 1989 at the 11th International Joint Conference on Artificial Intelligence held in Detroit, Michigan. At first, it was called “knowledge discovery in database” (KDD), which the author of this book used as the title of a research project to apply for a 1993 National Nature Science Fund. After 1996, a general consensus was reached on the use of data mining, which means the process of digging up valid, up-to-date, and potentially useful knowledge that is both friendly to people and can be understood by machines. Up until now, objects and tools for mining documents, voices, images, and the web have become popular in the information age, with related works and reference books available everywhere. The symposium on KDD, first initiated by the American Association for Artificial Intelligence in 1989, has been run as an annual international conference since 1995, with competitions organized and awards given. It should be particularly noted that, from the very beginning, data mining has been application-oriented. IBM, GTE, Microsoft, Silicon Graphics, Integral Solution, Thinking Machine, Datamind, Urban Science, AbTech, Unica Technologies successively developed some practical KDD business systems like BehaviorScan, Explorer, and MDT (Management Discovery Tool) for market analysis; Stock Selector and AI (Automated Investor) for financial investment; and Falcon, FAIS, and Clonedetector against fraud.
Overview of Modern Artificial Intelligence
Published in Mark Chang, Artificial Intelligence for Drug Development, Precision Medicine, and Healthcare, 2020
Biological evolution can be viewed as a learning process: biological organisms adapt to improve the probabilities of survival and having offspring in their environment. This implies that we can use biological evolutionary mechanisms as artificial learning algorithms. Genetic programming (GP) is exactly such a technique. Richard Forsyth (1981) demonstrated the successful evolution of small programs, represented as trees, to perform classification of crime scene evidence. In GP, computer programs are encoded as a set of genes that are then modified (evolved) using an evolutionary algorithm. The methods used to encode a computer program in an artificial chromosome and to evaluate its fitness with respect to the predefined task are central in the GP technique. The term “genetic programming” was coined by Goldberg in 1983 in his PhD dissertation (Goldberg, 1983). In 1988 John Koza patented his invention of a genetic algorithm (GA) for program evolution. This was followed by publication in the International Joint Conference on Artificial Intelligence. The series of four books by Koza collected many GP applications in 1992 and established GP. Koza (2010b) summarized 77 results where GP was human-competitive. GP has be used for software synthesis and repair, predictive modeling, data mining, financial modeling, and image processing, cellular encoding, and for mining DNA chip data from cancer patients (Langdon and Buxton, 2004). GP has been successfully used as an automatic programming tool, a machine learning tool and an automatic problem-solving engine. GP is especially useful in the domains where the exact form of the solution is not known in advance or when an approximate solution is acceptable. Some of the applications of GP are curve fitting, data modeling, symbolic regression, feature selection, and classification.
23rd RCRA International workshop on “Experimental evaluation of algorithms for solving problems with combinatorial explosion”
Published in Journal of Experimental & Theoretical Artificial Intelligence, 2018
Stefano Bistarelli, Andrea Formisano, Marco Maratea
Since the 2005 edition, the RCRA workshops have focussed on the theme of algorithms in Artificial Intelligence. These meetings have reached the objective to put together researchers coming from AI fields as diverse as constraint satisfaction, machine learning, logic languages, quantified satisfiability, planning, and scheduling, just to name a few. The event has gained more and more interest, first from the Italian community, then from the international one. In 2008, the workshop was co-located with the International Conference on Logic Programming (ICLP 2008), in 2010 the event was in association with the seventh International Conference on Integration of Artificial Intelligence and Operations Research techniques in Constraint Programming (CP-AI-OR 2010), whereas in 2011 it was a satellite workshop of the twenty-second International Joint Conference on Artificial Intelligence (IJCAI 2011). The 2012 and 2013 edition of the RCRA workshop was held in Rome, (in 2012 in association with the 12th AI*IA Symposium on Artificial Intelligence (AI*IA 2012), and in 2013 as a standalone event).
Design science research in construction management: multi-disciplinary collaboration on the SightPlan system
Published in Construction Management and Economics, 2020
As Ray was keen to explore the use of KBES and wanted us to be informed of the latest developments in the field, he had me attend the 9th International Joint Conference on Artificial Intelligence which happened to be nearby, in Los Angeles, California in 1985 (IJCAI 1985). Note that I had become aware of KBES only earlier that same year, so: all power to Ray to send me to this conference bright eyed and bushy tailed!