Introduction to Modern Artificial Intelligence
Topics include Intelligent Agents, Search and Problem Solving, Logic and Language, Reasoning and Uncertainty, and Learning
Artificial Intelligence, A Modern Approach Russell and Norvig Third Edition (2009/2010) Prentice Hall ISBN: 0-13-604259-7 http://aima.cs.berkeley.edu/
30-50 pages of the textbook
(CPSC 201 and CPSC 202) or permission of the instructor. All assignments are in Python.
Introduction to AI, Python for AI, Agent-based view of AI
Problem Solving and Search, Informed Search, Heuristic Search, Advanced Search, Game Playing, Adversarial Search, Genetic Algorithms, Constraint Satisfaction, Planning (if time)
Logical Agents, Predicate Logic, First Order Logic, Inference, Knowledge Representation, Natural Language Processing and Communication, Speech Processing (if time)
Quantifying Uncertainty, Intro to uncertainty, Probabilistic Reasoning, Bayesian Networks
Learning from Examples, Classification and Clustering, Markov Decision Processes, Neural Networks, Reinforcement Learning, Autonomous Cars
Introduction to AI Programming Languages for AI Agent-based view of AI Problem solving and search Informed Search Heuristic search Adversarial search Genetic algorithms Constraint satisfaction Intro to Logic and Logical agents Propositional Logic First order logic Inference in FOL Knowledge representation Intro to Communication and Perception Intro to uncertainty Probabilistic reasoning Bayesian Networks Supervised Learning Probabilistic reasoning over time (HMM+MDP) Natural Language Processing and Speech Neural networks, Deep Learning Reinforcement learning Autonomous cars Conclusion
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