We either know something or we don’t know it. Boolean 1 or 0: very limiting.
Degree of belief, regarded as probability, is more flexible as it can take any value between 0 and 1. Rather than “I know X”, I prefer “I believe X with probability P”.
This is my current approach to bot development: the bot’s “knowledge base” is actually a set of beliefs, each belief comprising a proposition and a probability value. (If I were truly Bayesian I’d use a beta probability distribution.) Since I’m training the bot using supervised learning, it believes whatever I tell it to believe. However, it needs to be able to link beliefs together in order to infer a belief value for a proposition it hasn’t actually been trained with. For example a donkey bot needs to be able to link the proposition “I am a donkey” with “I like carrots” to calculate a degree of belief in “Donkeys like carrots”. This is not as straightforward as it might seem.
David