CS 5881 - Artificial Intelligence

• Demonstrate an understanding of the principles of Formal Logic including Propositional and First Order Logic
• Conduct proofs of correctness in reasoning systems using the methods of Unification and Resolution
• Understand the techniques involved with reasoning in the presence of uncertainty
• Address the problems related to search, and its application to intelligent systems, including: game playing, decision making, and adversarial search
• Understand and apply modern machine learning techniques for supervised, unsupervised, and reinforcement learning

• A fundamental understanding of structured programming languages
• A fundamental understanding of data structures and algorithms
• A fundamental understanding of probability and statistics

• Problem Solving, Uninformed Search
• A* Search and Heuristic Functions
• Local Search
• Constraint Satisfaction
• Online Search
• Game Playing
• Logical Agents, Propositional Logic
• Forward Chaining, Backward Chaining, Knowledge Agents
• More Knowledge Based Agents
• First Order Logic
• First Order Inference
• Knowledge Representation
• Acting under uncertainty, axioms of probability, inference using joint distributions
• Bayes Networks
• Machine Learning
• Supervised learning: Naive Bayes, Decision Trees, and Neural Networks
• Unsupervised learning: Clustering with K-Means, K-Medoids, and Hierarchical Agglomerative clustering
• Collaborative filtering
• Reinforcement Learning
• Data mining
• Concept Learning and Inductive Hypothesis

• History, defining intelligence, grand challenges, biologically inspired computing
• Intelligent agents, uninformed search, informed search
• Knowledge based agents
• Machine learning