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Uncertainty

This lecture explores the fundamental concepts of acting under uncertainty, crucial for understanding Artificial Intelligence. We will cover key topics including probability theory, Bayes' Rule, and practical applications such as Nave Bayesian classifiers and Bayesian networks. Real-world agents, like those in poker or business decisions, often operate without complete information, making these concepts particularly relevant. The challenges of representation and uncertainty in decision-making will also be addressed, demonstrating the importance of probabilistic reasoning in AI systems.

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Uncertainty

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    1. Uncertainty Craig A. Struble, Ph.D. Department of Mathematics, Statistics, and Computer Science Marquette University

    2. COSC 159 - Fundamentals of AI 2 Overview Acting Under Uncertainty Introduction to Probability Bayes Rule Application - Nave Bayesian Classifier Bayesian Networks

    3. COSC 159 - Fundamentals of AI 3 Acting Under Uncertainty Real world agents rarely have access to the whole truth e.g. poker, Columbia explosion, business decisions, weather Even knowing whole truth, representation infeasible

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