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CS 1 – Introduction to Computer Science

CS 1 – Introduction to Computer Science. Introduction to the wonderful world of Dr. T Dr. Daniel Tauritz. Teaching. Artificial Intelligence (AI), in particular:

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CS 1 – Introduction to Computer Science

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  1. CS 1 – Introduction to Computer Science Introduction to the wonderful world of Dr. T Dr. Daniel Tauritz

  2. Teaching Artificial Intelligence (AI), in particular: • Introduction to Artificial Intelligence (CS347) – heuristic search, game theory, games (WS2002: Abalone, FS2003: Stratego), intelligent agents • Evolutionary Computation (CS401) – solving REALLY hard problems (FS2002 samples, FS2003 samples)

  3. Research Natural Computation Lab Problem domain: Computer Security Approaches: • Discrete Mathematics • Artificial Intelligence (Game Theory) • Evolutionary Computation • Neural Networks • Fuzzy Logic

  4. Base courses for AI (1) Mathematics • Math 8/21/22 Calculus & Geometry I,II,III • CS 158 Discrete Mathematics for CS • Math 203/208 Matrix/Linear Algebra • CS 228 Intro to Numerical Methods Optional mathematics • CS 328 & 329 Object-Oriented Numerical Modeling I & II

  5. Base courses for AI (2) Programming & Algorithms • CS 53/54 Introduction to Programming • CS 153 Data Structures I • CS 253 Data Structures II Advanced theory • CS 330 Automata Theory • CS 355 Analysis of Algorithms

  6. AI courses • CS 347 Artificial Intelligence • CS 378 Neural Networks & Applications • CS 401 Evolutionary Computation • CS 404 Data Mining & Knowledge Discovery • CS 447 Advanced Topics in AI • EE 338 Fuzzy Logic Control • EMAN 478 Advanced Neural Networks

  7. Evolutionary Computation • Inspired by Darwin’s theory of natural selection and survival of the fittest and Mendel’s laws of heredity (genetics) • A population of individuals in an environment becomes a set of trial solutions for a problem • Fitness indicates quality of solution • Genes represented by a data type

  8. Example problem Given the function f(x,y) = x2y + 5xy -3xy2 -5 <= x <= 5 and -5 <= y <= 5 for what integer values of x and y is f(x,y) minimal?

  9. Evolutionary Algorithm (1) • Trial solution: (x,y) • Genes represented by integers • Fitness function: -f(x,y) • Population size: 4 • Number of offspring: 2 • Competition: remove the 2 individuals with the lowest fitness value

  10. Evolutionary Algorithm (2) • Selection: in first step select with 50% chance fittest individual, in second step with 50% second fittest individual, etc. If no individuals selected, select fittest. Genetic operators: • 1-point crossover with 50% chance • single unit increment or decrement mutation with 50% chance

  11. UMR ACM SIG Security Come to the Intro Meeting 7:00pm, Wednesday, Sep. 10th Room 216, CS Building Free Pizza

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