At a time when utilities companies are facing flat demand, new regulations and competition from new entrants into the energy market, a bleeding-edge A.I. technology is emerging as the go-to solution for forward-thinking enterprises. Download this free whitepaper from Next IT to learn why self-service with a concierge touch is helping the largest utilities companies lift customer engagement and drive down the costs of doing business.
We introduce a new interpretation of two related notions - conditional utility and utility independence. Unlike the traditional interpretation, the new interpretation renders the notions the direct analogues of their probabilistic counterparts. To capture these notions formally, we appeal to the notion of utility distribution, introduced in previous paper. We show that utility distributions, which have a structure that is identical to that of probability distributions, can be viewed as a special case of an additive multiattribute utility functions, and show how this special case permits us to capture the novel senses of conditional utility and utility independence. Finally, we present the notion of utility networks, which do for utilities what Bayesian networks do for probabilities. Specifically, utility networks exploit the new interpretation of conditional utility and utility independence to compactly represent a utility distribution.
You may get a call about a late phone, gas or electric bill. Should you pay right away? Chances are good that this call is a scam. According to Hiya, a company that makes caller blocking software, bogus utility callers claim to be calling from ConEd, Duke Energy, Georgia Power and Consumers Energy. Scammers even claim to be calling from General Electric, which isn't even a utility company.