It is an interesting question.
After working in this filed (confluence of New AI [a.k.a deep learning, reinforcement learning, and deep reinforcement learning], ML, Soft Computing, Evolutionary Computing, Fuzzy Computing, Applied Statistics, and Optimization) for 30 years, I come to the following conclusion:
Prescriptive analytics, which aims at providing insights to the domain expert/decision maker, predominantly involves formulating and solving linear and nonlinear optimization problems. Thus, it is distinct from descriptive and predictive analytics. Quite easily one can relate predictive analytics (which comprises data/text/web mining techniques- that in turn involve ML. new AI and applied statistical techniques) to the catch-all word AI, used by you.
There is an umpteen number of use cases one can cite to explain the usefulness of prescriptive analytics without relating it to AI.
Therefore, AI and prescriptive analytics can co-exist without actually being related to each other.
Having said that Tabu search, a metaheuristic, is inspired by ideas from AI, while Hopfield neural network is designed to solve combinatorial optimization problems. These are the two links that come to my mind which relate these two fields.
Best regards
Ravi
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Dr. Ravi Vadlamani
Professor and Head, Center of Excellence in Analytics,
Inst for Dev. and Res.in Banking Tech (IDRBT), Hyderabad
Hyderabad, India
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Original Message:
Sent: 10-19-2018 15:42
From: Jane Mather
Subject: AI and Prescriptive Analytics
Should we include prescriptive analytics in AI? Does the audience matter?
I've been trying to find an answer to this question.
Prescriptive analytics certainly provides intelligence for questions people have. For quantifiable challenges, prescriptive analytics can do many things even better than what a person could do. But as far as my reading shows, prescriptive analytics doesn't fit into the traditional AI definitions, which reflect machine learning and solutions to more subjective problems.
When I try to explain what I do to a general audience, however, AI seems to make more sense than prescriptive analytics. AI, providing a way to automate tasks, is interesting and what they need. Prescriptive analytics results in puzzled stares.
Any suggestions or comments?
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Jane Mather, Ph.D.
Principal, Critical Core
Fraser CO
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