20 min listen
LM101-007: How to Reason About Uncertain Events using Fuzzy Set Theory and Fuzzy Measure Theory
LM101-007: How to Reason About Uncertain Events using Fuzzy Set Theory and Fuzzy Measure Theory
ratings:
Length:
27 minutes
Released:
Jun 23, 2014
Format:
Podcast episode
Description
Learning Machines 101 - A Gentle Introduction to Artificial Intelligence and Machine Learning
Episode Summary: In real life, there is no certainty. There are always exceptions. In this episode, two methods are discussed for making inferences in uncertain environments. In fuzzy set theory, a smart machine has certain beliefs about imprecisely defined concepts. In fuzzy measure theory, a smart machine has beliefs about precisely defined concepts but some beliefs are stronger. Read More »
The post LM101-007: How to Reason About Uncertain Events using Fuzzy Set Theory and Fuzzy Measure Theory appeared first on Learning Machines 101.
Episode Summary: In real life, there is no certainty. There are always exceptions. In this episode, two methods are discussed for making inferences in uncertain environments. In fuzzy set theory, a smart machine has certain beliefs about imprecisely defined concepts. In fuzzy measure theory, a smart machine has beliefs about precisely defined concepts but some beliefs are stronger. Read More »
The post LM101-007: How to Reason About Uncertain Events using Fuzzy Set Theory and Fuzzy Measure Theory appeared first on Learning Machines 101.
Released:
Jun 23, 2014
Format:
Podcast episode
Titles in the series (85)
LM101-003: How to Represent Knowledge using Logical Rules: Episode Summary: In this episode we will learn how to use .rules. to represent knowledge. We discuss how this works in practice and we explain how these ideas are implemented in a special architecture called the production system. by Learning Machines 101