10Th Genetic Improvement Workshop (GI 2021 @ ICSE) Chairs' Welcome
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Challenges in Cybersecurity: Lessons from Biological Defense Systems
1 Challenges in cybersecurity: Lessons from biological defense systems Edward Schroma, Ann Kinzigb,c, Stephanie Forrestd,e,f, Andrea L. Grahama, Simon A. Levina*, Carl T. Bergstromg, Carlos Castillo-Chavezh, James P. Collinsb, Rob J. de Boeri, Adam Doupée,j, Roya Ensafik, Stuart Feldmanl, Bryan T. Grenfella,m, J. Alex Haldermank,n, Silvie Huijbenb, Carlo Maleyp,d, Melanie Mosesr,s,f, Alan S. Perelsont,f, Charles Perringsb, Joshua Plotkinu, Jennifer Rexfordv, Mohit Tiwariw a Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ 08544, bSchool of Life Sciences, Arizona State University, Tempe, AZ 85287, cJulie Ann Wrigley Global Institute of Sustainability, Arizona State University, Tempe, AZ 85287, dBiodesign Center for Biocomputation, Security and Society, Arizona State University, Tempe, AZ 85287, eSchool of Computing, Informatics and Decision Sciences Engineering, Arizona State University, Tempe, AZ 85287, fSanta Fe Institute, Santa Fe, NM 87501, gDepartment of Biology, University of Washington, Seattle, WA 98195, hRetired Professor, Arizona State University, Tempe, AZ 85287, iTheoretical Biology and Bioinformatics, Utrecht University, 3584 CH Utrecht, The Netherlands, jCenter for Cybersecurity and Digital Forensics, Global Security Initiative, Arizona State University, Tempe, AZ 85287, kDepartment of Electrical Engineering and Computer Science, Computer Science and Engineering Division, University of Michigan, Ann Arbor, MI 48109, lSchmidt Futures, New York, NY 10011, mPrinceton School of Public and International -
Neutrality and Epistasis in Program Space
2018 ACM/IEEE 4th International Genetic Improvement Workshop Neutrality and Epistasis in Program Space Joseph Renzullo Westley Weimer Arizona State University University of Michigan Tempe, Arizona Ann Arbor, Michigan [email protected] [email protected] Melanie Moses Stephanie Forrest∗ University of New Mexico Arizona State University Albuquerque, New Mexico Tempe, Arizona [email protected] [email protected] ABSTRACT 1 INTRODUCTION Neutral networks in biology often contain diverse solutions with Genetic Improvement of software is more likely to succeed when the equal fitness, which can be useful when environments (require- search algorithm is well-matched to the fitness landscape, whether ments) change over time. In this paper, we present a method for for repairing bugs or improving a nonfunctional property of the studying neutral networks in software. In these networks, we find program. The fitness landscape integrates information about the multiple solutions to held-out test cases (latent bugs), suggesting problem to be solved, its representation, and the search operators that neutral software networks also exhibit relevant diversity. We that are used. Neutral spaces are an important component of many also observe instances of positive epistasis between random mu- fitness landscapes, and we hypothesize that they help determine tations, i.e. interactions that collectively increase fitness. Positive the dynamics and ultimate success of genetic improvement. The epistasis is rare as a fraction of the total search space but significant topology of the neutral space, i.e. the network of programs (nodes) as a fraction of the objective space: 9% of the repairs we found that are equivalent under the fitness metric and connected by sin- to look (and 4.63% across all programs analyzed) were produced gle applications of the search operators (edges) is referred to as a by positive interactions between mutations. -
1 CURRICULUM VITA Melanie Mitchell Santa Fe Institute 1399
CURRICULUM VITA Melanie Mitchell Santa Fe Institute 1399 Hyde Park Road Santa Fe, NM 87501 Email: [email protected] Web site: melaniemitcHell.me RESEARCH EXPERIENCE AND INTERESTS Artificial intelligence, macHine learning, biologically inspired computing, cognitive science, and complex systems. GRADUATE EDUCATION Ph.D. in Computer Science, 1990, University of MicHigan. Dissertation advisor: Douglas R. Hofstadter Dissertation title: Copycat: A Computer Model of High-Level Perception and Conceptual Slippage in Analogy-Making. PROFESSIONAL EMPLOYMENT Davis Professor, Santa Fe Institute, 2020–present. Professor, Portland State University, Department of Computer Science, 2004–present. (On leave, 2019-2021.) External Professor, Santa Fe Institute, 2000–present. Professor, July-September 2004; Associate Professor, August 2002-June 2004, OGI ScHool of Science and Engineering, Oregon HealtH & Science University, Department of Computer Science and Engineering. Staff Member, Santa Fe Institute, 2000–2002. Technical Staff Member, Los Alamos National Laboratory, BiopHysics Group, 1999–2000. Research Professor and Director of the Adaptive Computation Program, Santa Fe Institute, 1992–1999. Postdoctoral Scholar, University of MicHigan, Department of Electrical Engineering and Computer Science, 1990 –1992. 1 HONORS AND AWARDS Herbert A. Simon Award, International Conference on Complex Systems, 2020. Medal of Excellence, Portland International Center for Management of Engineering and Technology, 2019. Winner of Phi Beta Kappa Society 2010 Science Book Award for Complexity: A Guided Tour. Complexity: A Guided Tour named by Amazon.com as #3 of the 10 best science books of 2009. Complexity: A Guided Tour longlisted (one of 12) for the 2010 Royal Society Science Book Prize. Ulam Memorial Lectureship, Santa Fe Institute, 1997 (Annual honorary lectureship for three public lectures on Complex Systems).