28.1 Representing Probabilities in Networks
Much human reasoning is about propositions and quantities that are uncertain. Our beliefs about many things are provisional (that is, subject to change) and qualified (that is, having various levels of confidence). AI systems, too, need to be able to deal with uncertain information. An AI agent’s facts, statements, and rules should most appropriately be thought of as provisional and qualified. After all, some of its information is provided by humans and some originates from sensors with limited precision and reliability. Yet, much of the early work in AI ignored the uncertain nature of knowledge. In fact, Marvin Minsky observed that his edited volume of early AI papers contained ...