Assessing Information Heard on the Radio

Much work in AI is devoted to the problem of how computers can acquire beliefs about the world through perception, but little effort is devoted to the problem of how computers can acquire beliefs through testimony. This paper is part of a continuing project whose ultimate goal is that of constructing an implementable model of how agents acquire knowledge through testimony. In particular, it looks at how agents acquire information from the radio and many factors are identified that may cause an agent to override the defeasible rule to believe what he hears.