MEER 111 Global Research Solving Real-World Problems

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MEER 111 – Global Research Solving Real-World Problems with Evolutionary Algorithms Daniel Tauritz, Ph. D. Associate Professor of Computer Science

Algorithm An algorithm is a sequence of well-defined instructions that can be executed in a finite amount of time in order to solve some problem.

Optimization Algorithm An optimization algorithm is an algorithm which takes as input a solution space, an objective function which maps each point in the solution space to a linearly ordered set, and a desired goal element in the set.

Stochastic Algorithm A stochastic algorithm is an algorithm which when executed multiple times with the same input, produces different outputs drawn from some underlying probability distribution.

Evolutionary Algorithm A stochastic optimization algorithm inspired by genetics and natural evolution theory.

Deriving Gas-Phase Exposure History through Computationally Evolved Inverse Diffusion Analysis • Joshua M. Eads • Former undergraduate student in Computer Science • Daniel Tauritz • Associate Professor of Computer Science • Glenn Morrison • Associate Professor of Environmental Engineering • Ekaterina Smorodkina • Former Ph. D. Student in Computer Science

Introduction Find Contaminants and Fix Issues Examine Indoor Exposure History Unexplained Sickness

Background • Indoor air pollution top five environmental • • • health risks $160 billion could be saved every year by improving indoor air quality Current exposure history is inadequate A reliable method is needed to determine past contamination levels and times

Problem Statement • A forward diffusion differential equation predicts concentration in materials after exposure • An inverse diffusion equation finds the timing and intensity of previous gas contamination • Knowledge of early exposures would greatly strengthen epidemiological conclusions

Gas-phase concentration history and material absorption

Proposed Solution • Use Genetic Programming (GP) as a directed search for inverse equation • Fitness based on x^5 + x^4 - tan(y) / pi x^2 + sin(x) sin(cos(x+y)^2) sin(x+y) + e^(x^2) 5 x^2 + 12 x - 4 x^2 - sin(x) X + Sin / forward equation ?

Related Research • It has been proven that the inverse • • equation exists Symbolic regression with GP has successfully found both differential equations and inverse functions Similar inverse problems in thermodynamics and geothermal research have been solved

Interdisciplinary Work • Collaboration between Environmental Engineering, Computer Science, and Math Parent Selection Candidate Solutions Competition Population Reproduction Fitness Genetic Programming Algorithm Forward Diffusion Equation

Genetic Programming Background + Y = X^2 + Sin( X * Pi ) Si n * X X * X Pi

Summary • Ability to characterize exposure history will enhance ability to assess health risks of chemical exposure

Coevolutionary Automated Software Correction (CASC) ISC Sponsored Project Ph. D. student: Josh Wilkerson

Objective: Find a way to automate the process of software testing and correction. Approach: Create Coevolutionary Automated Software Correction (CASC) system which will take a software artifact as input and produce a corrected version of the software artifact as output.