Download FS2008

CS 1 – Introduction to
Computer Science
Introduction to the wonderful world
of Dr. T
Daniel Tauritz, Ph.D.
Associate Professor of Computer Science
Teaching
• CS158 Discrete Mathematics
• CS347 Introduction to Artificial
Intelligence
• CS348 Evolutionary Computing
• CS448 Advanced Evolutionary
Computing
CS158 – Discrete Mathematics
The mathematical foundations
for creating discrete
abstractions of the real-world
and algorithms to operate on
those abstract structures.
CS347 – Introduction to AI
Problem solving through state
space search (search
algorithms which operate on
abstract representations of the
real-world)
AI Tournament
CS348 – Evolutionary Computing
Problem solving through
stochastic, population-based
search inspired by natural
evolution theory (algorithms
which operate on abstract
representations of the realworld)
CS448 – Advanced Evolutionary
Computing
Individual research projects
The goal of scientific research is
to add to the body of
knowledge
Design & Application of Novel Evolutionary Algorithms for Real-World Problem Solving
Evolutionary Algorithm (EA)
Research Challenges
 How to design user-friendly EAs?
 How to prevent premature convergence?
 How to efficiently identify high-quality
strategy parameters?
 How to prove convergence to exactly, or within
ε of, the global optimum?
 How to prevent cycling, disengagement, and
mediocre stability in CoEAs?
 How to overcome the curse of dimensionality
in evolutionary computing?
 How to compute objective fitness values in
CoEAs?
Problem
Description
Evolutionary
Problem Solving
Population
Initialization
Strategy
Parameters
Fitness Evaluation
Problem Specific
Black Box
Reproduction
Evolutionary
Cycle
Competition
Current Research Projects
Parameterless Evolutionary Algorithms
Coevolutionary Automated Software Correction
Critical Infrastructure Protection via Computational Arms-Races
Inverse Diffusion Analysis Employing Genetic Programming
Deriving Historical Information from Dynamic, Diffusive,
Environmental Systems
Autonomous Evolutionary Algorithms
Co-Optimization
Evolutionary Rule-Based Intrusion Detection Systems
no
Termination
Criteria Met?
Fitness Evaluation
Solution
yes
Sample Application Areas
Black Box Optimization
Combinatorial Problem Solving
Configuration Optimization
Modeling / System Identification
Automated Problem Solving
Automated Software Engineering
Co-Learning / Optimization
Simulating Natural Evolution