Artificial Computational Intelligence

17 lectures

Foundations of intelligent agents, search, knowledge representation, and reasoning under uncertainty.

01Lecture 01 · Introduction to Artificial Intelligence

02Lecture 02 · Intelligent Agents and Problem Solving

03Lecture 03 · Uninformed and Informed Search

04Lecture 04 · Heuristics: Evaluation, Design, and Relaxation

05Lecture 05 · Local Search Algorithms and Introduction to Evolutionary Algorithms

06Lecture 06 · Genetic Algorithms, Ant Colony Optimization, and Neural Architecture Search

07Lecture 07 · Neural Architecture Search and Game Playing

08Lecture 08 · Static Evaluation, Alpha-Beta Pruning, and Monte Carlo Tree Search

09Lecture 09 · Knowledge Representation Using Logics

10Lecture 10 · Inference Techniques in Propositional Logic

11Lecture 11 · First Order Logic, Forward Chaining, and Backward Chaining

12Lecture 12 · Bayesian Networks

13Lecture 13 · Bayesian Networks: D-Separation, Variable Elimination, and Approximate Inferencing

14Lecture 14 · Temporal Models and Hidden Markov Models

15Lecture 15 · Hidden Markov Model Algorithms and Multi-Agent Decision Making

16Lecture 16 · Multi-Agent Decision Making: Cooperative Game Theory

17Lecture 17 · Mechanism Design, Auctions, Voting, Bargaining and Ethics in AI

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