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CS408: Advanced Artificial Intelligence
Sections
Course Introduction
Unit 1: Intelligent Agents and Problems of AI
Unit 2: Solving Problems by Searching
Unit 3: Logical Agents and Knowledge Representation
Unit 4: Learning
Unit 5: Philosophical Foundations of AI
Final Exam
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-- General --
-- Course Introduction --
-- Unit 1: Intelligent Agents and Problems of AI --
-- 1.1: Is It an Agent, or Just a Program? --
-- 1.1.1: John Lloyd on Intelligent Agents --
-- 1.1.2: Stan Franklin - A Cognitive Theory of Everything --
-- 1.2: Overview of AI General Problems --
-- 1.2.1: Knowledge Representation --
-- 1.2.2: Planning --
-- 1.2.3: Learning --
-- 1.3: Approaches to AI --
-- 1.3.1: Systems with General Intelligence --
-- 1.4: Agents in Code --
-- Unit 2: Solving Problems by Searching --
-- 2.1.1: Graph Definition --
-- 2.1.2: Binary Tree --
-- 2.1.3: Example Problem: Minimum Spanning Tree --
-- 2.2.1: Binary Search Trees --
-- 2.2.2: Red-Black Trees --
-- 2.2.3: Skip List --
-- 2.3.1: Depth-first Search --
-- 2.3.2: Breadth-First Search --
-- 2.3.3: Dijkstra's Algorithm --
-- 2.4: Search Algorithms in General --
-- 2.5: Basic Notions in Graph Theory --
-- 2.6: Graph Examples in Code --
-- Unit 3: Logical Agents and Knowledge Representation --
-- 3.1: Logic Programming --
-- 3.2.1: Bayesian Network --
-- 3.2.2: Hidden Markov Model --
-- 3.2.3.1: Kalman Filter --
-- 3.2.3.2: Decision Theory --
-- 3.3: Knowledge Representation and Reasoning --
-- 3.4: Coding Drills --
-- Unit 4: Learning --
-- 4.1: Machine Learning --
-- 4.1.1: Reinforcement Learning --
-- 4.1.2: Machine Learning, Probability, and Graphical Models --
-- 4.2.1: Introduction to Neural Networks --
-- 4.2.2: Feedforward Neural Networks --
-- 4.2.3: Radial Basis Function Networks --
-- 4.2.4: The Perceptron --
-- 4.2.5: Vector Quantization (VQ) Networks --
-- 4.2.6: Hopfield Network --
-- 4.3.1: Kernel Methods --
-- 4.3.2: k-nearest Neighbor Algorithm --
-- 4.3.3: Mixture Model --
-- 4.3.4: Naive Bayes Classifier --
-- 4.3.5: Decision Tree --
-- 4.3.6: Kernels and Gaussian Processes --
-- 4.4: Machine Learning Coding Drills --
-- Unit 5: Philosophical Foundations of AI --
-- 5.1.1: Philosophical Issues and Turing Test --
-- 5.1.2: Computing Machinery and Intelligence --
-- 5.1.3: Turing Machine --
-- 5.1.4: Computability and Incompleteness --
-- 5.2: Important Propositions in the Philosophy of AI --
-- 5.3: Machine Consciousness --
-- Final Exam --
CS408: Certificate Final Exam
CS408: Proctored Final Exam
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Final Exam
Quiz
CS408: Certificate Final Exam
Quiz
CS408: Proctored Final Exam