Presentation on theme: "Tools: Computers and IT. VB, VBA, Excel, InterDev, Etc. Humans: Decision Making Process Algorithms: Math/Flow Chart stuff that helps the tools help the."— Presentation transcript:
Tools: Computers and IT. VB, VBA, Excel, InterDev, Etc. Humans: Decision Making Process Algorithms: Math/Flow Chart stuff that helps the tools help the humans make decisions. Artificial Intelligence and Neural Networks DSS Data: Facts pertinent to the decision at hand.
MACHINE INTELLIGENCE Will computers become as smart as humans within the next 50 years?
IBM’S “DEEP BLUE” CHESS PLAYING COMPUTER A couple of years ago (1997), IBM’s Deep Blue computer beat world chess champion Gary Kasporov in a chess match. Does that mean Deep Blue is “smarter” than Kasporov when it comes to playing chess?
IBM’S “DEEP BLUE” CHESS PLAYING COMPUTER What if I told you Deep Blue has to look at a million times more scenarios than Kasporov to settle on a move? See http://www.ishipress.com/hamlet.htm
Artificial Intelligence Artificial intelligence is behavior by a machine that, if performed by a human being, would be called intelligent "Artificial Intelligence is the study of how to make computers do things at which, at the moment, people are better" (Rich and Knight ) AI is basically a theory of how the human mind works (Mark Fox)
Objectives of Artificial Intelligence (Winston and Prendergast ) Make machines smarter (primary goal) Understand what intelligence is (Nobel Laureate purpose) Make machines more useful (entrepreneurial purpose)
Signs of Intelligence Learn or understand from experience Make sense out of ambiguous or contradictory messages Respond quickly and successfully to new situations Use reasoning to solve problems
Signs of Intelligence (cont’d) Deal with perplexing situations Understand and Infer in ordinary, rational ways Apply knowledge to manipulate the environment Think and reason Recognize the relative importance of different elements in a situation
Turing Test for Intelligence A computer can be considered to be smart only when a human interviewer, “conversing” with both an unseen human being and an unseen computer, could not determine which is which
AI Computing Based on symbolic representation and manipulation A symbol is a letter, word, or number represents objects, processes, and their relationships Objects can be people, things, ideas, concepts, events, or statements of fact Create a symbolic knowledge base
AI Computing (cont’d) Uses various processes to manipulate the symbols to generate advice or a recommendation AI reasons or infers with the knowledge base by search and pattern matching Hunts for answers (Algorithms often used in search)
AI software and FAQs http://www.cs.cmu.edu/Groups/AI/html/faqs/ai/ (fairly techie) American Association for Artificial Intelligence http://www.aaai.org (fairly general) PC Artificial Intelligence magazine http://www.pcai.com/pcai (just right for OMIS 661, in my opinion) The AI Laboratory at MIT: http://www.ai.mit.edu Some interesting AI Web Destinations
An Overview of Neural Computing Constructing computers that mimic certain processing capabilities of the human brain Knowledge representations based on – Massive parallel processing – Fast retrieval of large amounts of information – The ability to recognize patterns based on historical cases Neural Computing = Artificial Neural Networks (ANNs)
Learning Three Tasks (over-simplified) 1. Compute Outputs 2. Compare Outputs with Desired Targets 3. Adjust Weights and Repeat the Process
Set the weights by either some rules or randomly Set Delta = Error = actual output minus desired output for a given set of inputs Objective is to Minimize the Delta (Error) Change the weights to reduce the Delta Information processing: pattern recognition Different learning algorithms
Benefits of Neural Networks Usefulness for pattern recognition, learning, classification, generalization and abstraction, and the interpretation of incomplete and noisy inputs Specifically - character, speech and visual recognition Potential to provide some of human problem solving characteristics Ability to tackle new kinds of problems Robustness Fast processing speed Flexibility and ease of maintenance Powerful hybrid systems
Limitations of Neural Networks Do not do well at tasks that are not done well by people Lack explanation capabilities Limitations and expense of hardware technology restrict most applications to software simulations Training times can be excessive and tedious Usually requires large amounts of training and test data
Some interesting Neural Web Destinations Brainmaker http://www.calsci.com Neural Works Professional II Plus Neuralware, Inc