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

2. Goals & Actions Have to do versus Choose to do Goals Actions Commitments

3. Teaching Artificial Intelligence (AI), in particular: Introduction to Artificial Intelligence (CS347) – heuristic search, game theory, games (WS2002: Abalone, FS2003: Stratego,FS2004: Chess), intelligent agentsWS2002 FS2003 Evolutionary Computation (CS401) – solving REALLY hard problems (FS2002 samples, FS2003 samples)FS2002 samplesFS2003 samples

4. Research Natural Computation Lab Problem domain: Critical Infrastructure Protection (Computer Security, Power Grid) Approaches: Artificial Intelligence (Game Theory, Search) Evolutionary Computation Neural Networks Fuzzy Logic

5. 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

6. 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 (optional) CS 330 Automata Theory CS 355 Analysis of Algorithms

7. 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 CpE 301 Computational Intelligence CpE 401 Adaptive Critic Designs EMAN 478 Advanced Neural Networks

8. UMR ACM SIG Security Come to the Intro MeetingIntro Meeting 6:00pm, Wednesday, Sep. 15 th Room 209A, CS Building