<p>Episode Summary: This episode focusses upon how an intelligent system can represent beliefs about its environment using fuzzy measure theory. Probability theory is introduced as a special case of fuzzy measure theory which is consistent with classical laws of logical inference.</p>

Episode Summary: This episode focusses upon how an intelligent system can represent beliefs about its environment using fuzzy measure theory. Probability theory is introduced as a special case of fuzzy measure theory which is consistent with classical laws of logical inference.

LM101-008: How to Represent Beliefs Using Probability Theory

Smart machines based upon the principles of artificial intelligence and machine learning are now prevalent in our everyday life.  For example, artificially intelligent systems recognize our voices, sort our pictures, make purchasing suggestions, and can automatically fly planes and drive cars. In this podcast series, we examine such questions such as: How do these devices work? Where do they come from? And how can we make them even smarter and more human-like? These are the questions that will be addressed in this podcast series!

Science

Technology

Mathematics

Smart machines based upon the principles of artificial intelligence and machine learning are now prevalent in our everyday life. For example, artificially intelligent systems recognize our voices, sort our pictures, make purchasing suggestions, and can automatically fly planes and drive cars. In this podcast series, we examine such questions such as: How do these devices work? Where do they come from? And how can we make them even smarter and more human-like? These are the questions that will be addressed in this podcast series!

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LM101-008: How to Represent Beliefs Using Probability Theory

LM101-008: How to Represent Beliefs Using Probability Theory