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|Session Name:||Improving AI Decision Modeling Through Utility Theory|
|Speaker(s):||Kevin Dill, Dave Mark|
|Company Name(s):||Lockheed Martin, Intrinsic Algorithm|
|Track / Format:||AI Summit|
|Overview:||The 'if/then' statement has been the workhorse of decision modeling longer than digital computing. Unfortunately, the harsh transition from yes to no often expresses itself through behavior in ways that are just as harsh. Utility theory has roots in areas such as psychology, economics, sociology, and classical game theory. By applying the science of utility theory with algorithmic techniques such as response curves, population distributions, and weighted randoms, we can improve the modeling of the underlying brain of our agents, broaden the potential decision space, and even manage edge cases that other decision systems stumble over.|