Publications | Moshe Sipper

Publications✒️

Google Scholar ◦ GP Bibliography

BOOKS (books page)

M. Sipper, Fredric: A Collection of Flash Fiction, Amazon, 2017
M. Sipper, Daniel Max and the King in the Tower, Amazon, 2014
M. Sipper, The Peaceful Affair, Amazon, 2013
M. Sipper, Xor: The Shape of Darkness, Amazon, 2012
M. Sipper, Evolved to Win, Lulu, 2011
M. Sipper, Machine Nature: The Coming Age of Bio-Inspired Computing, McGraw-Hill, New York, 2002
M. Sipper, Evolution of Parallel Cellular Machines: The Cellular Programming Approach, Springer-Verlag, Heidelberg, 1997

PRESS

אחד הפחדים הכי גדולים שלנו: כך אפשר למנוע מתקפות סייבר על מכוניות אוטונומיות (YouTube, Channel 1 News, 2024)
נהיגה קטלנית: מדבקות הסייבר שמסוגלות לתקוף את הטסלה שלכם (Israel Hayom, 2024)
5 Scientists At The Forefront Of Computing And AI (Ezvid, 2021)
The Aliens Have Landed—But They’re Not Smart Enough to Take Over (Newsweek, 2019)
אנחנו לא לבד (iBGU, May 2019)
The aliens have landed—but they’re not smart enough to take over (Newsweek, 2019)
These Researchers Want the People to Seize the Means of AI Production (Motherboard, 2017)
אלגוריתם אבולוציוני משפר ומשכלל תוכנות ללא התערבות בני אדם (ISF, 2016)
האם גם מחשבים מתפתחים אבולוציונית? (iBGU, 2014)
בדרך לסרט שליחות קטלנית: פותחו מחשבים שמתפתחים לבד (nrg, 2014)
מחקר: ניתן לשדרג את “מנת המשכל” של מחשבים עד כדי סיכוי מוחשי לנצח בני אנוש (The People, 2014)
אלגוריתם אבולוציוני מסייע למחשבים (hadoctor, 2014)
פרס זהב בתחרות יוקרתית לחוקרים מאונ’ בן-גוריון (news1, 2011)
נחסמת במגרש החנייה? (BGU Journal, 2009)
דארווין דיגיטלי (BGU Journal, 2009)
Biology’s Gift to a Complex World (The Scientist, 2008)
האבולוציה בשירות המחשב (mynet, 2008)
כשהמתכנתים פגשו את דארווין (Hayadan, 2008)
ישראלים המציאו אלגוריתם שחמט המחקה את האבולוציה (ynet, 2007)
המטריקס – בינתיים זה רק סרט (Nana, Part 1, 2004)
לך אל הנמלה, חוקר (Nana, Part 2, 2004)
Machine Nature (New Scientist, 2002)
Computer Design Meets Darwin (Science, 1997)

MEDIUM
(sampling of my Medium articles—all the rest available here)

WEBPAGES

SLIDES

EDITED

D. Loiacono and M. Sipper, Eds., Genetic Programming and Evolvable Machines: Special Issue on GECCO Competitions, vol. 15, issue 4, December 2014
Co-editor of N. Krasnogor et al., Proceedings of the 13th Annual Conference on Genetic and Evolutionary Computation, ACM, New York, NY, 2011
M. Sipper and M. Giacobini, Eds., Genetic Programming and Evolvable Machines: Special Section on Evolutionary Computation in Games, vol. 9, no. 4, 2008
J. Kroc, R. Vollmar, M. Sipper, & S. El Yacoubi, Eds., Journal of Cellular Automata: Special Issue — Modelling of Complex Systems by Cellular Automata, vol. 1, no. 2, 2006
E. Ruppin, J. A. Reggia, and M. Sipper, Eds., Artificial Intelligence in Medicine: Special Issue — Evolutionary Computation in Medicine, vol. 19, no. 1, May 2000
M. Sipper and D. Mange, Eds., IEEE Transactions on Evolutionary Computation: Special Issue — From Biology to Hardware and Back, vol. 3, no. 3, September 1999
M. Sipper, G. Tempesti, D. Mange, and E. Sanchez, Eds., Artificial Life: Special Issue on Self-Replication, vol. 4, no. 3, Summer 1998
M. Sipper, D. Mange, and A. Pérez-Uribe, Eds., Proceedings of The Second International Conference on Evolvable Systems: From Biology to Hardware (ICES98), vol. 1478 of Lecture Notes in Computer Science, Springer-Verlag, Heidelberg, 1998

PAPERS

2024

T. Alter, R. Lapid, M. Sipper, On the Robustness of Kolmogorov-Arnold Networks: An Adversarial Perspective, arXiv:2408.13809, 2024.
E. Shem-Tov, M. Sipper, A. Elyasaf, Deep Learning-Based Operators for Evolutionary Algorithms, arXiv:2407.10477, 2024.
R. Lapid, A. Dubin, M. Sipper, Fortify the Guardian, Not the Treasure: Resilient Adversarial Detectors, Mathematics. 2024; 12(22):3451. (arXiv:2404.12120)
B. Pinhasov, R. Lapid, R. Ohayon, M. Sipper, Y. Aperstein, XAI-Based Detection of Adversarial Attacks on Deepfake Detectors, Transactions on Machine Learning Research, 2024. (TMLR link).
M. Sipper, Task and Explanation Network, arXiv:2401.01732, 2024.
M. Sipper and R. Lapid, What’s in an AI’s Mind’s Eye? We Must Know, in IEEE Computer, vol. 57, pp. 99-103, July 2024.
Moshe Sipper, Achiya Elyasaf, Tomer Halperin, Zvika Haramaty, Raz Lapid, Eyal Segal, Itai Tzruia, Snir Vitrack Tamam, A Melting Pot of Evolution and Learning, Genetic Programming Theory and Practice XX, pages 143-158, Springer, 2024. (arXiv)

2023

R. Lapid, R. Langberg, M. Sipper, Open Sesame! Universal Black Box Jailbreaking of Large Language Models, arXiv:2309.01446, 2023. Short version: ICLR 2024 Workshop on Secure and Trustworthy Large Language Models (SeT LLM @ ICLR 2024). Long version: Appl. Sci. 2024, 14(16), 7150.
I. Tzruia, T. Halperin, M. Sipper, A. Elyasaf, Fitness Approximation through Machine Learning, arXiv:2309.03318, 2023.
R. Lapid and M. Sipper, I See Dead People: Gray-Box Adversarial Attack on Image-To-Text Models, arXiv:2306.07591, 5th Workshop on Machine Learning for CyberSecurity (ECMLPKDD 2023).
R. Lapid, E. Mizrahi, M. Sipper, Patch of Invisibility: Naturalistic Black-Box Adversarial Attacks on Object Detectors, arXiv:2303.04238, 2023, 6th Workshop on Machine Learning for CyberSecurity (ECMLPKDD 2024).
M. Sipper, Classy Ensemble: A Novel Ensemble Algorithm for Classification, arXiv:2302.10580, 2023.
S. Vitrack Tamam, R. Lapid, M. Sipper, Foiling Explanations in Deep Neural Networks, Transactions on Machine Learning Research, 2023.
M. Sipper, T. Halperin, I. Tzruia, and A. Elyasaf, EC-KitY: Evolutionary Computation Tool Kit in Python with Seamless Machine Learning Integration, SoftwareX, Volume 22, May 2023, 101381.
M. Sipper, Combining Deep Learning with Good Old-Fashioned Machine Learning, SN Computer Science, 4, 85 (2023). (arXiv:2207.03757)

2022

R. Lapid, Z. Haramaty, M. Sipper, An Evolutionary, Gradient-Free, Query-Efficient, Black-Box Algorithm for Generating Adversarial Instances in Deep Networks, Algorithms, 15(11):407, 2022. (arXiv:2208.08297)
E. Segal and M. Sipper, Adaptive Combination of a Genetic Algorithm and Novelty Search for Deep Neuroevolution, in Proceedings of the 14th International Joint Conference on Computational Intelligence, pages 143-150, 2022.
M. Sipper, High Per Parameter: A Large-Scale Study of Hyperparameter Tuning for Machine Learning Algorithms, Algorithms, 15(9):315, 2022.
M. Sipper, Artificial General Intelligence: Pressure Cooker or Crucible?, in Computer, vol. 55, no. 7, pp. 92-96, July 2022.
M. Sipper, J. H. Moore, R. J. Urbanowicz, Automatically balancing model accuracy and complexity using Solution and Fitness Evolution (SAFE), arXiv:2206.15409, 2022.
R. Lapid and M. Sipper, Evolution of Activation Functions for Deep Learning-Based Image Classification, in: Proceedings of the Genetic and Evolutionary Computation Conference Companion, GECCO ’22, Association for Computing Machinery, New York, NY, USA, 2022, p. 2113–2121. (arxiv)
M. Sipper, Binary and Multinomial Classification through Evolutionary Symbolic Regression, in: Proceedings of the Genetic and Evolutionary Computation Conference Companion, GECCO ’22, Association for Computing Machinery, New York, NY, USA, 2022, p. 300–303. (arxiv)
R. Poliansky, M. Sipper, A. Elyasaf, From requirements to source code: Evolution of behavioral programs, Applied Sciences, 12(3):1587, 2022.
M. Sipper and J. H. Moore, AddGBoost: A Gradient Boosting-Style Algorithm Based on Strong Learners, Machine Learning with Applications, Volume 7, 100243, March 2022.

2021

M. Sipper, Neural Networks with À La Carte Selection of Activation Functions, SN Computer Science, 2, 470 (2021). (Springer link)
M. Sipper and J. H. Moore, Symbolic-regression boosting, Genetic Programming and Evolvable Machines, 22:357–381, 2021. (Springer link)
M. Sipper and J. H. Moore, Conservation Machine Learning: A Case Study of Random Forests, Nature Scientific Reports, 11, 3629 (2021).

2020

M. Sipper and J. H. Moore, Conservation machine learning, BioData Mining 13, 9 (2020).
R. J. Urbanowicz and M. Sipper, Evolutionary algorithms in biomedical data mining: challenges, solutions, and frontiers, in Proceedings of the 2020 Genetic and Evolutionary Computation Conference Companion (GECCO ’20), Association for Computing Machinery, New York, NY, USA, pp. 1224-1253, 2020. (published tutorial slides)
M. Sipper and J. H. Moore, Genetic programming theory and practice: A fifteen-year trajectory, Genetic Programming and Evolvable Machines, vol. 21, pp 169–179, 2020. (alternate link)
M. Sipper and J. H. Moore, Gamorithm, IEEE Transactions on Games, Volume 12 , Issue 1, March 2020, pp. 115-118 (IEEE link)
M. Sipper, J. H. Moore, and R. J. Urbanowicz, New pathways in coevolutionary computation, Genetic Programming Theory and Practice XVII (GPTP 2019), Springer Nature Switzerland AG, 2020.
M. Sipper, J. H. Moore, and R. J. Urbanowicz, Coevolving Artistic Images Using OMNIREP, In: Romero J., Ekárt A., Martins T., Correia J. (eds) Artificial Intelligence in Music, Sound, Art and Design. EvoMUSART 2020, pp. 165-178. Lecture Notes in Computer Science, vol. 12103. Springer, Cham.

2019

J. H. Moore, R. S. Olson, Y. Chen, and M. Sipper, Discovering test statistics using genetic programming, In Proceedings of the Genetic and Evolutionary Computation Conference, GECCO 2019
M. Sipper, W. Fu, K. Ahuja, and J. H. Moore, Correction to: Investigating the parameter space of evolutionary algorithms, BioData Mining, 12:22, 2019
M. Sipper and J. H. Moore, OMNIREP: Originating meaning by coevolving encodings and representations, Memetic Computing, September 2019, Volume 11, Issue 3, pp 251–261 (alternate link)
M. Sipper, J. H. Moore, and R. J. Urbanowicz, Solution and fitness evolution (SAFE): A study of multiobjective problems, In 2019 IEEE Congress on Evolutionary Computation (CEC), pp. 1868-1874. IEEE, 2019. (alternate link)
M. Sipper, J. H. Moore, and R. J. Urbanowicz, Solution and fitness evolution (SAFE): Coevolving solutions and their objective functions, In: Sekanina L., Hu T., Lourenço N., Richter H., García-Sánchez P. (eds), EuroGP 2019, pp 146-161. Lecture Notes in Computer Science, vol 11451. Springer, Cham, 2019 (alternate link)
J. H. Moore, R. S. Olson, Y. Chen, and M. Sipper, Automated discovery of test statistics using genetic programming, Genetic Programming and Evolvable Machines, vol. 20, issue 1, pp. 127-137, 2019 (alternate link)

2018

M. Sipper, R. J. Urbanowicz, and J. H. Moore, To know the objective is not (necessarily) to know the objective function, BioData Mining, 2018, 11:21
R. S. Olson, M. Sipper, W. La Cava, S. Tartarone, S. Vitale, W. Fu, P. Orzechowski, R. J. Urbanowicz, J. H. Holmes, and J. H. Moore, A System for Accessible Artificial Intelligence, In: Banzhaf W., Olson R., Tozier W., Riolo R. (eds) Genetic Programming Theory and Practice XV. Genetic and Evolutionary Computation series. pp. 121-134, 2018, Springer, Cham (alternate link)
P. Orzechowski, M. Sipper, X. Huang, and J. H. Moore, EBIC: an evolutionary-based parallel biclustering algorithm for pattern discovery, Bioinformatics, bty401, 2018 (arXiv)
P. Orzechowski, M. Sipper, X. Huang, and J. H. Moore, EBIC: a next-generation, evolutionary-based parallel biclustering method, in GECCO ’18: Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2018, pp. 59-60, ACM, New York, NY
J. H. Moore and M. Sipper, Grammatical evolution strategies for bioinformatics and systems genomics, C. Ryan, M. O’Neill, J. J. Collins (eds.), Handbook of Grammatical Evolution, Springer International Publishing, pp. 395-405, 2018 (alternate link)
M. Sipper, W. Fu, K. Ahuja, and J. H. Moore, Investigating the parameter space of evolutionary algorithms, BioData Mining, 11:2, 2018 (alternate link)
M. Sipper, W. Fu, K. Ahuja, and J. H. Moore, Evolutionary computation: an investigation of parameter space, in GECCO ’18: Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2018, pp. 29-30, ACM, New York, NY
I. Azaria, A. Elyasaf, and M. Sipper, Evolving artificial general intelligence for video game controllers, in Genetic Programming Theory and Practice XIV, 2018, pp. 53-63, Springer, Cham (alternate link)

2017

M. Sipper and J. H. Moore, Artificial intelligence: more human with human, BioData Mining, vol. 10, pp. 34-35, 2017
M. Sipper, Review of “Paul Rendell: Turing machine universality of the Game of Life”, Genetic Programming and Evolvable Machines, vol. 18, issue 1, pp. 115-117, 2017
M. Sipper, R. S. Olson, and J. H. Moore, Evolutionary computation: The next major transition of artificial intelligence?, BioData Mining, vol. 10, pp. 26-28, 2017

2016

A. Elyasaf, P. Vaks, N. Milo, M. Sipper, and M. Ziv-Ukelson, Learning heuristics for mining RNA sequence-structure motifs, in Genetic Programming Theory and Practice XIII (GPTP 2015), R. Riolo, W. Worzel, M. Kotanchek, A. Kordon, Eds. 2016, pp. 21-38, Springer
M. Sipper, Constructing counters through evolution, in Designing Beauty: The Art of Cellular Automata, A. Adamatzky and G. J. Martínez, Eds., pp., 75-78, Springer, Germany, 2016
G. Barabash Katz, A. Benbassat, M. Sipper, Development of Counting Ability: An Evolutionary Computation Point of View, in Continuous Issues in Numerical Cognition: How Many or How Much, A. Henik, Ed., pp. 123-145, Elsevier, 2016

2015

D. Ashlock, S. Colton, M. Eladhari, M. Van Kreveld, P. Lanzi, and M. Sipper, Bold automatic game design, in Artificial and Computational Intelligence in Games: Integration, S. M. Lucas, M. Mateas, M. Preuss, P. Spronck, and J. Togelius, Eds., pp. 212-213, Schloss Dagstuhl—Leibniz-Zentrum fuer Informatik, Germany, 2015
A. Paiva, S. Samothrakis, T. Schaul, N. Shaker, M. Sipper, J. Togelius, G. Yannakakis, and F. Zambetta, Algorithms that learn to play like people, in Artificial and Computational Intelligence in Games: Integration, S. M. Lucas, M. Mateas, M. Preuss, P. Spronck, and J. Togelius, Eds., pp. 222-223, Schloss Dagstuhl—Leibniz-Zentrum fuer Informatik, Germany, 2015

2014

K. Kannappan, L. Spector, M. Sipper, T. Helmuth, W. Lacava, J. Wisdom, and O. Bernstein, Analyzing a Decade of Human-Competitive (“HUMIE”) Winners: What Can We Learn?, in Genetic Programming Theory and Practice XII (GPTP 2014), R. Riolo, B. Worzel, and M. Kotanchek, Eds. 2014, Springer
M. Sipper, Commentary on ‘Genetic Programming and Emergence’, Genetic Programming and Evolvable Machines, vol. 15, no. 1, pp. 91-93, 2014
A. Elyasaf and M. Sipper, Software review: the HeuristicLab framework, Genetic Programming and Evolvable Machines, vol. 15, no. 2, pp. 215-218, 2014
M. Sipper and A. Elyasaf, Lunch Isn’t Free — But Cells Are: Evolving FreeCell Players, SIGEVOlution, vol. 6, issue 3-4, pp. 2-10, 2014
A. Benbassat and M. Sipper, EvoMCTS: A scalable approach for general game learning, IEEE Transactions on Computational Intelligence and AI in Games, vol. 6, issue 4, pp. 1-13, December 2014

2013

G. Barabash Katz, A. Benbassat, L. Diesendruck, M. Sipper, and A. Henik, From size perception to counting: An evolutionary computation point of view, in Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2013) Companion, 2013, ACM, pp. 1675-1678
A. Benbassat and M. Sipper, Evolving artificial neural networks with FINCH, in Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2013) Companion, 2013, ACM, pp. 1719-1720
A. Elyasaf , M. Orlov, and M. Sipper, A HeuristicLab evolutionary algorithm for FINCH, in Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2013) Companion, 2013, ACM, pp. 1727-1728
A. Elyasaf and M. Sipper, HH-Evolver: A system for domain-specific, hyper-heuristic evolution, in Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2013) Companion, 2013, ACM, pp. 1285-1291
A. Benbassat and M. Sipper, EvoMCTS: Enhancing MCTS-based players through genetic programming, Proceedings of IEEE Conference on Computational Intelligence and Games (IEEE CIG), 2013, pp. 1-8, IEEE
P. I. Cowling, M. Buro, M. Bida, A. Botea, B. Bouzy, M. V. Butz, P. Hingston, H. Muñoz-Avila, D. Nau, and M. Sipper, Search in real-time video games, in Artificial and Computational Intelligence in Games, S. M. Lucas, M. Mateas, M. Preuss, P. Spronck, and J. Togelius, Eds., pp. 1-19, Schloss Dagstuhl—Leibniz-Zentrum fuer Informatik, Dagstuhl, Germany, 2013

2012

M. Sipper, Darwinian Software Engineering: The Short Term, the Middle Ground, and the Long Haul, Ubiquity Symposium, December 2012
A. Benbassat and M. Sipper, Evolving Both Search and Strategy for Reversi Players using Genetic Programming, in Proceedings of IEEE Conference on Computational Intelligence and Games (IEEE CIG 2012)
A. Elyasaf, A. Hauptman, and M. Sipper, Evolutionary Design of FreeCell Solvers, in IEEE Transactions on Computational Intelligence and AI in Games, vol. 4, no. 4, pp. 270-281, 2012
A. Benbassat and M. Sipper, Evolving Players that Use Selective Game-Tree Search with Genetic Programming, in GECCO’12 Companion, T. Soule et al., Eds. 2012, ACM
A. Benbassat, A. Elyasaf, and M. Sipper, More or Less? Two Approaches to Evolving Game-Playing Strategies, in Genetic Programming Theory and Practice X (GPTP 2012), 2012, Springer

2011

K. Wolfson, S. Zakov, M. Sipper, and M. Ziv-Ukelson, Have your spaghetti and eat it too: Evolutionary algorithmics and post-evolutionary analysis, Genetic Programming and Evolvable Machines, Volume 12, Number 2, pp. 121-160, 2011
M. Orlov, C. Bregman, and M. Sipper, Automatic evolution of Java-written game heuristics, in Proceedings of 3rd International Symposium on Search Based Software Engineering (SSBSE 2011), M. B. Cohen and M. O. Cinneide, Eds, 2011, p. 277. Springer-Verlag Berlin Heidelberg
M. Orlov and M. Sipper, Flight of the FINCH through the Java wilderness, IEEE Transactions on Evolutionary Computation, vol. 15, no. 2, pp. 166-182, 2011
A. Benbassat and M. Sipper, Evolving board-game players with genetic programming, in Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2011) Workshops, N. Krasnogor et al., Eds., 2011, pp. 739-742, ACM
M. Sipper, Let the Games Evolve!, in Genetic Programming Theory and Practice IX (GPTP 2011), R. Riolo, T. McConaghy, and E. Vladislavleva, Eds, 2011, pp. 17-36, Springer-Verlag, Heidelberg
A. Elyasaf, Y. Zaritsky, A. Hauptman, and M. Sipper, Evolving solvers for FreeCell and the sliding-tile puzzle, in Proceedings of the Fourth Annual Symposium on Combinatorial Search (SoCS 2011), 2011
Y. Shichel and M. Sipper, GP-RARS: Evolving controllers for the Robot Auto Racing Simulator, Memetic Computing, Volume 3, Number 2, pp. 89-99, 2011
A. Elyasaf, A. Hauptman, and M. Sipper, GA-FreeCell: Evolving solvers for the game of FreeCell, in Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2011), 2011, ACM

2010

M. Orlov and M. Sipper, FINCH: A system for evolving Java (bytecode), in Genetic Programming Theory and Practice VIII (GPTP 2010), R. Riolo, T. McConaghy, and E. Vladislavleva, Eds. 2010, pp. 1-16, Springer
A. Hauptman, A. Elyasaf, and M. Sipper, Evolving hyper heuristic-based solvers for Rush Hour and FreeCell, in Proceedings of the Third Annual Symposium on Combinatorial Search (SoCS 2010), 2010, pp. 149-150
M. Sipper, Evolutionary games, in Encyclopedia of Machine Learning, C. Sammut and G. I. Webb, Eds., Springer-Verlag, Heidelberg, 2010, pp. 362-369, Springer
A. Benbassat and M. Sipper, Evolving lose-checkers players using genetic programming, in Proceedings of IEEE Conference on Computational Intelligence and Games (IEEE CIG 2010), 2010

2009

K. Wolfson and M. Sipper, Evolving efficient list search algorithms, in Artificial Evolution: Proceedings of 9th International Conference (EA 2009), P. Collet, N. Monmarche, P. Legrand, M. Schoenauer, and E. Lutton, Eds. 2009, vol. 5975 of Lecture Notes in Computer Science, pp. 158-169, Springer-Verlag, Heidelberg
M. Orlov and M. Sipper, Genetic programming in the wild: Evolving unrestricted bytecode, in Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2009), pp. 1043-1050, ACM
M. Orlov, M. Sipper, and A. Hauptman, Genetic and evolutionary algorithms and programming: General introduction and application to game playing, in Encyclopedia of Complexity and Systems Science, R. A. Meyers, Ed., Springer-Verlag, Heidelberg, 2009
I. Kadar, O. Ben-Shahar, and M. Sipper, Evolution of a local boundary detector for natural images via genetic programming and texture cues, in Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2009), pp. 1887-1888, ACM
A. Hauptman, A. Elyasaf, M. Sipper, and A. Karmon, GP-Rush: Using genetic programming to evolve solvers for the Rush Hour puzzle, in Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2009), pp. 955-962, ACM

2008

M. Orlov and M. Sipper, Evolutionary software improvement for instruction set meta-evolution, in Proceedings of Workshop and Summer School on Evolutionary Computing (WSSEC 2008), IEEE Press
I. Kadar, O. Ben-Shahar, and M. Sipper, Evolving boundary detectors for natural images via genetic programming, in Proceedings of the 19th International Conference on Pattern Recognition (ICPR 2008)
A. Glazer and M. Sipper, Evolving an automatic defect classification tool, in Applications of Evolutionary Computing: Proceedings of EvoWorkshops 2008, M. Giacobini et al., Eds. 2008, vol. 4974 of Lecture Notes in Computer Science, pp. 194-203, Springer-Verlag, Heidelberg
M. Sipper, Cluster-dense networks, International Journal of Modern Physics C, vol. 19, no. 6, pp. 939-946, 2008

2007

S. Michal, T. Ivry, O. S. Cohen, M. Sipper, and D. Barash, Finding a common motif of RNA sequences using genetic programming: The GeRNAMo system, IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 4, no. 4, pp. 596-610, Oct.-Dec. 2007
A. Hauptman and M. Sipper, Evolution of an efficient search algorithm for the mate-in-n problem in chess, in Proceedings of 10th European Conference on Genetic Programming (EuroGP2007), M. Ebner, M. O’Neill, A. Ekárt, L. Vanneschi, A. I. Esparcia-Alcázar, Eds. 2007, vol. 4445 ofLecture Notes in Computer Science, pp. 78-89, Springer-Verlag, Heidelberg
A. Hauptman and M. Sipper, Emergence of complex strategies in the evolution of chess endgame players, Advances in Complex Systems, vol. 10, suppl. no. 1, pp. 35-59, 2007
M. Sipper, Y. Azaria, A. Hauptman, and Y. Shichel, Designing an evolutionary strategizing machine for game playing and beyond, IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews, vol. 37, no. 4, pp. 583-593, July 2007

2006

M. Sipper, Artificial life: From life-as-we-know-it to life-as-it-could-be, in Life As We Know It, J. Seckbach, Ed., vol. 9 of Cellular Origin, Life in Extreme Habitats and Astrobiology, pp. 707-718. Springer-Verlag, Heidelberg, 2006
M. Sipper, Evolving game-playing strategies with genetic programming, ERCIM (European Research Consortium for Informatics and Mathematics) News, no. 64, pp. 28-29, January 2006
S. Sharabi and M. Sipper, GP-Sumo: Using genetic programming to evolve sumobots, Genetic Programming and Evolvable Machines, vol. 7, no. 3, pp. 211-230, October 2006
M. Sipper, Book review of Kinematic Self-Replicating Machines by Robert A. Freitas, Jr. and Ralph C. Merkle, Artificial Life Journal, vol. 12, no. 1, pp. 187-188, Winter 2006

2005

Y. Shichel, E. Ziserman, and M. Sipper, GP-Robocode: Using genetic programming to evolve robocode players, in Proceedings of 8th European Conference on Genetic Programming (EuroGP2005), M. Keijzer, A. Tettamanzi, P. Collet, J. van Hemert, and M. Tomassini, Eds. 2005, vol. 3447 of Lecture Notes in Computer Science, pp. 143-154, Springer-Verlag, Heidelberg
A. Hauptman and M. Sipper, GP-EndChess: Using genetic programming to evolve chess endgame players, in Proceedings of 8th European Conference on Genetic Programming (EuroGP2005), M. Keijzer, A. Tettamanzi, P. Collet, J. van Hemert, and M. Tomassini, Eds. 2005, vol. 3447 of Lecture Notes in Computer Science, pp. 120-131, Springer-Verlag, Heidelberg
Y. Azaria and M. Sipper, GP-Gammon: Genetically programming backgammon players, Genetic Programming and Evolvable Machines, vol. 6, no. 3, pp. 283-300, September 2005
Y. Azaria and M. Sipper, GP-Gammon: Using genetic programming to evolve backgammon players, in Proceedings of 8th European Conference on Genetic Programming (EuroGP2005), M. Keijzer, A. Tettamanzi, P. Collet, J. van Hemert, and M. Tomassini, Eds. 2005, vol. 3447 of Lecture Notes in Computer Science, pp. 132-141, Springer-Verlag, Heidelberg

2004

Y. Hasson and M. Sipper, A novel ant algorithm for solving the minimum broadcast time problem, in Eighth International Conference on Parallel Problem Solving from Nature (PPSN 8), X. Yao, E. Burke, J. A. Lozano, J. Smith, J. J. Merelo-Guervos, J. A. Bullinaria, J. Rowe, P. Tino, A. Kaban, and H. -P. Schwefel, Eds. 2004, vol. 3242 of Lecture Notes in Computer Science, pp. 501-510, Springer-Verlag, Berlin
B. Naveh, M. Sipper, D. Lancet, and B. Shenhav, Lipidia: An artificial chemistry of self-replicating assemblies of lipid-like molecules, in Artificial Life IX: Proceedings of the 9th International Conference on the Simulation and Synthesis of Living Systems, J. Pollack, M. Bedau, P. Husbands, T. Ikegami, and R. A. Watson, Eds. 2004, pp. 466-471, The MIT Press, Cambridge, Massachusetts
A. Stauffer and M. Sipper, The data and signals cellular automation and its application to growing structures, Artificial Life, vol. 10, no. 4, pp. 463-477, Fall 2004
M. Sipper, Reifying building blocks in evolutionary algorithms, AISB Quarterly, no. 118, pp. 3, Autumn 2004
A. Zaritsky and M. Sipper, The preservation of favoured building blocks in the struggle for fitness: The puzzle algorithm, IEEE Transactions on Evolutionary Computation, vol. 8, no. 5, pp. 443-455, October 2004
A. Zaritsky and M. Sipper, Coevolving solutions to the shortest common superstring problem, Biosystems, vol. 76, nos. 1-3, pp. 209-216, August-October 2004

2003

A. Stauffer and M. Sipper, Biomorphs implemented as a data and signals cellular automaton, in Advances in Artificial Life: Proceedings of the 7th European Conference on Artificial Life (ECAL 2003), W. Banzhaf, T. Christaller, P. Dittrich, J. T. Kim, and J. Ziegler, Eds. 2003, vol. 2801 of Lecture Notes in Artificial Intelligence, pp. 724-732, Springer-Verlag, Heidelberg
A. Gal, G. Mahal, and M. Sipper, Evolutionary plantographics, Artificial Life, vol. 9, no. 2, pp. 191-205, Spring 2003
A. Stauffer and M. Sipper, Data and signals: A new kind of cellular automaton for growing systems, Proceedings of 5th NASA/DoD Workshop on Evolvable Hardware (EH 2003), 2003, IEEE Computer Society, Los Alamitos, California
C.-A. Peña-Reyes and M. Sipper, Fuzzy CoCo: Balancing accuracy and interpretability of fuzzy models by means of coevolution, in Accuracy Improvements in Linguistic Fuzzy Modeling, J. Casillas, O. Cordón, F. Herrera, and L. Magdalena, Eds., vol. 129 of Studies in Fuzziness and Soft Computing, chapter 6, pp. 119-146. Springer-Verlag, Heidelberg, 2003
A. Stauffer and M. Sipper, Interactive self-replicating, self-incrementing and self-decrementing loops, in Artificial Life VIII: Proceedings of the 8th International Conference on the Simulation and Synthesis of Living Systems, R. K. Standish, M. A. Bedau, and H. A. Abbass, Eds. 2003, pp. 53-56, The MIT Press, Cambridge, Massachusetts

2002

D. Mange, A. Stauffer, G. Tempesti, and M. Sipper, Penser d autres formes de vie, in Sur les traces du vivant,, F. Raulin-Cerceau et al., Ed., pp. 255-268. Le pommier, Paris, 2002
C.-A. Peña-Reyes and M. Sipper, Combining evolutionary and fuzzy techniques in medical diagnosis, Computational Intelligence Processing in Medical Diagnosis, M. Schmitt, H.-N. Teodorescu, As. Jain, Aj. Jain, S. Jain, and L. C. Jain, Eds., chapter 14, pp. 391-426. Physica-Verlag, Heidelberg, 2002
C.-A. Peña-Reyes, M. Sipper, and L. Prieto, Sensitive, specific, and interpretable: Evolving a fuzzy mammographic-interpretation assessment tool, Proceedings of 2002 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE2002). 2002, pp. 837-842, IEEE Press, Piscataway, NJ
C. Teuscher and M. Sipper, Hypercomputation: Hype or computation?, Communications of the ACM, vol. 45, no. 8, pp. 23-24, August 2002
A. Stauffer and M. Sipper, Emergence of self-replicating loops in an interactive, hardware-implemented Game-of-Life environment, Proceedings of Fifth International Conference on Cellular Automata for Research and Industry (ACRI 2002), S. Bandini, B. Chopard, and M. Tomassini, Eds. 2002, vol. 2493 of Lecture Notes in Computer Science, pp. 123-131, Springer-Verlag, Berlin
A. Stauffer and M. Sipper, An interactive self-replicator implemented in hardware, Artificial Life, vol. 8, no. 2, pp. 175-183, Spring 2002
M. Sipper and J. A. Reggia, Roboter, die sich selbst vermehren, Spektrum der Wissenschaft, pp. 26-33, April 2002

2001

E. M. A. Ronald and M. Sipper, Intelligence is not enough: On the socialization of talking machines, Minds and Machines, vol. 11, no. 4, pp. 567-576, November 2001
E. M. A. Ronald and M. Sipper, Surprise versus unsurprise: Implications of emergence in robotics, Robotics and Autonomous Systems, vol. 37, no. 1, pp. 19-24, October 2001
M. S. Capcarrère and M. Sipper, Necessary conditions for density classification by cellular automata, Physical Review E, vol. 64, no. 3, pp. 036113/1-036113/4, September 2001
C.-A. Peña-Reyes and M. Sipper, Fuzzy CoCo: A cooperative-coevolutionary approach to fuzzy modeling, IEEE Transactions on Fuzzy Systems, vol. 9, no. 5, pp. 727-737, October 2001
C.-A. Peña-Reyes and M. Sipper, The flowering of Fuzzy CoCo: Evolving fuzzy iris classifiers, in Proceedings of 5th International Conference on Artificial Neural Networks and Genetic Algorithms (ICANNGA 2001), V. Kurkova, N. C. Steele, R. Neruda, and M. Karny, Eds. 2001, pp. 304-307, Springer-Verlag, Vienna
M. Sipper, On the origin of environments by means of natural selection, AI Magazine, vol. 22, no. 4, pp. 133-140, Winter 2001
A. Stauffer and M. Sipper, Externally controllable and destructible self-replicating loops, in Advances in Artificial Life: Proceedings of the 6th European Conference on Artificial Life (ECAL 2001), J. Kelemen and P. Sosik, Eds. 2001, vol. 2159 of Lecture Notes in Artificial Intelligence, pp. 282-291, Springer-Verlag, Heidelberg
M. Sipper and J. A. Reggia, Go forth and replicate, Scientific American, vol. 285, no. 2, pp. 26-35, August 2001

2000

E. M. A. Ronald and M. Sipper, What use is a Turing chatterbox?, Communications of the ACM, vol. 43, no. 10, pp. 21-23, October 2000
E. M. A. Ronald and M. Sipper, Engineering, emergent engineering, and artificial life: Unsurprise, unsurprising surprise, and surprising surprise, in Artificial Life VII: Proceedings of the Seventh International Conference on Artificial Life, M. A. Bedau, J. S. McCaskill, N. H. Packard, and S. Rasmussen, Eds. 2000, pp. 523-528, The MIT Press, Cambridge, Massachusetts
C.-A. Peña-Reyes and M. Sipper, Evolutionary computation in medicine: An overview, Artificial Intelligence in Medicine, vol. 19, no. 1, pp. 1-23, May 2000
C.-A. Peña-Reyes and M. Sipper, Applying Fuzzy CoCo to breast cancer diagnosis, in Proceedings of the 2000 Congress on Evolutionary Computation (CEC00). 2000, vol. 2, pp. 1168-1175, IEEE Press, Piscataway, NJ
M. Tomassini, M. Sipper, and M. Perrenoud, On the generation of high-quality random numbers by two-dimensional cellular automata, IEEE Transactions on Computers, vol. 49, no. 10, pp. 1146-1151, October 2000
E. M. A. Ronald and M. Sipper, The challenge of tamperproof internet computing, IEEE Computer, vol. 33, no. 9, pp. 98-99, September 2000
M. Sipper, A success story or an old wives’ tale? On judging experiments in evolutionary computation, Complexity, vol. 5, no. 4, pp. 31-33, 2000
M. Sipper and E. M. A. Ronald, A new species of hardware, IEEE Spectrum, vol. 37, no. 3, pp. 59-64, March 2000
M. Sipper, E. Sanchez, J.-O. Haenni, J.-L. Beuchat, A. Stauffer, and A. Pérez-Uribe, From configurable circuits to bio-inspired systems, in Intelligent Systems and Interfaces, H.-N. Teodorescu, D. Mlynek, A. Kandel, and H.-J. Zimmermann, Eds., vol. 15 of Intelligent Technologies Series. Kluwer Academic Publishers, Boston, 2000
D. Mange, M. Sipper, A. Stauffer, and G. Tempesti, Toward Robust Integrated Circuits: The Embryonics Approach, Proceedings of the IEEE, vol. 88, no. 4, pp. 516-541, April 2000
D. Mange, M. Sipper, A. Stauffer, and G. Tempesti, Toward self-repairing and self-replicating hardware: The embryonics approach, in Proceedings of the Second NASA/DoD Workshop on Evolvable Hardware, J. Lohn, A. Stoica, D. Keymeulen, and S. Colombano, Eds. 2000, pp. 205-214, IEEE Computer Society, Los Alamitos, California
R. Levy, S. Lepri, E. Sanchez, G. Ritter, and M. Sipper, Slate of the art: An evolving FPGA-based board for handwritten-digit recognition, in Proceedings of the Second NASA/DoD Workshop on Evolvable Hardware, J. Lohn, A. Stoica, D. Keymeulen, and S. Colombano, Eds. 2000, pp. 237-243, IEEE Computer Society, Los Alamitos, California
M. Sipper and E. Sanchez, Configurable chips meld software and hardware, IEEE Computer, vol. 33, no. 1, pp. 120-121, January 2000
C. Teuscher, E. Sanchez, and M. Sipper, Romero’s odyssey to Santa Fe: From simulation to real life, in Robotic and Manufacturing Systems: Recent Results in Research, Development and Applications, M. Jamshidi, A. A. Maciejewski, R. Lumia, and S. Nahavandi, Eds. 2000, vol. 10 of TSI Press Series: Proceedings of the World Automation Congress, pp. 262-267, TSI Press, Albuquerque, NM
H. F. Restrepo, D. Mange, and M. Sipper, A self-replicating universal Turing machine: From von Neumann’s dream to new embryonic circuits, in Artificial Life VII: Proceedings of the Seventh International Conference on Artificial Life, M. A. Bedau, J. S. McCaskill, N. H. Packard, and S. Rasmussen, Eds. 2000, pp. 3-12, The MIT Press, Cambridge, Massachusetts

1999

E. M. A. Ronald, M. Sipper, and M. S. Capcarrère, Design, observation, surprise! A test of emergence, Artificial Life, vol. 5, no. 3, pp. 225-239, Summer 1999
E. M. A. Ronald, M. Sipper, and M. S. Capcarrère, Testing for emergence in artificial life, in Advances in Artificial Life: Proceedings of the 5th European Conference on Artificial Life (ECAL’99), D. Floreano, J.-D. Nicoud, and F. Mondada, Eds. 1999, vol. 1674 of Lecture Notes in Artificial Intelligence, pp. 13-20, Springer-Verlag, Heidelberg
C.-A. Peña-Reyes and M. Sipper, A fuzzy-genetic approach to breast cancer diagnosis, Artificial Intelligence in Medicine, vol. 17, no. 2, pp. 131-155, October 1999
C.-A. Peña-Reyes and M. Sipper, Designing breast cancer diagnostic systems via a hybrid fuzzy-genetic methodology, in Proceedings of 1999 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE’99), 1999, vol. I, pp. 135-139, IEEE Press, Piscataway, NJ
M. Tomassini, M. Sipper, M. Zolla, and M. Perrenoud, Generating high-quality random numbers in parallel by cellular automata, Future Generation Computer Systems, vol. 16, no. 2-3, pp. 291-305, December 1999
M. Sipper, The emergence of cellular computing, IEEE Computer, vol. 32, no. 7. pp. 18-26, July 1999
M. S. Capcarrère, M. Tomassini, A. G. B. Tettamanzi, and M. Sipper, A statistical study of a class of cellular evolutionary algorithms, Evolutionary Computation, vol. 7, no. 3, pp. 255-274, Fall 1999
M. Perrenoud, M. Tomassini, M. Sipper, and M. Zolla, Evolving high-quality random number generators, in Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-99), W. Banzhaf, J. Daida, A. E. Eiben, M. H. Garzon, V. Honavar, M. Jakiela, and R. E. Smith, Eds. 1999, vol. 1, p. 804, Morgan Kaufmann Publishers, San Francisco, California
M. Sipper and M. Tomassini, Computation in artificially evolved, non-uniform cellular automata, Theoretical Computer Science, vol. 217, no. 1, pp. 81-98, March 1999
M. Sipper, Notes on the origin of evolutionary computation, Complexity, vol. 4, no. 5, pp. 15-21, May/June 1999
E. M. A. Ronald and M. Sipper, Why must computers make us feel blue, see red, turn white, and black out?, IEEE Spectrum, vol. 36, no. 9, pp. 28-31, September 1999
D. Mange, M. Sipper, and P. Marchal, Embryonic electronics, BioSystems, vol. 51, no. 3, pp. 145-152, September 1999
M. Sipper, D. Mange, and E. Sanchez, Quo vadis evolvable hardware?, Communications of the ACM, vol. 42, no. 4, pp. 50-56, April 1999
E. Sanchez, M. Sipper, J.-O. Haenni, J.-L. Beuchat, A. Stauffer, and A. Pérez-Uribe, Static and dynamic configurable systems, IEEE Transaction on Computers, vol. 48, no. 6, pp. 556-564, June 1999

1998

M. Sipper, Fifty years of research on self-replication: An overview, Artificial Life, vol. 4, no. 3, pp. 237-257, Summer 1998
D. Mange and M. Sipper, Von neumann’s quintessential message: Genotype + ribotype = phenotype, Artificial Life, vol. 4, no. 3, pp. 225-227, Summer 1998
A. Stauffer and M. Sipper, L-hardware: Modeling and implementing cellular development using L-systems, in Bio-Inspired Computing Machines: Toward Novel Computational Architectures, M. Tomassini and D. Mange, Eds., pp. 269-287. Presses Polytechniques et Universitaires Romandes, Lausanne, Switzerland, 1998
A. Stauffer and M. Sipper, Modeling cellular development using L-systems, in Proceedings of The Second International Conference on Evolvable Systems: From Biology to Hardware (ICES98), M. Sipper, D. Mange, and A. Pérez-Uribe, Eds. 1998, vol. 1478 of Lecture Notes in Computer Science, pp. 196-205, Springer-Verlag, Heidelberg
I. Meilijson, E. Ruppin, and M. Sipper, Fast computation in Hamming and Hopfield networks, in Algorithms and Architectures, C. T. Leondes, Ed., vol. 1 of Neural Network Systems Techniques and Applications, pp. 123-154. Academic Press, New York, 1998
C.-A. Peña-Reyes and M. Sipper, Evolving fuzzy rules for breast cancer diagnosis, in Proceedings of 1998 International Symposium on Nonlinear Theory and its Applications (NOLTA’98). 1998, vol. 2, pp. 369-372, Presses Polytechniques et Universitaires Romandes, Lausanne, Switzerland
M. Sipper and M. Tomassini, An introduction to cellular automata, in Bio-Inspired Computing Machines: Toward Novel Computational Architectures, M. Tomassini and D. Mange, Eds. , pp. 49-58. Presses Polytechniques et Universitaires Romandes, Lausanne, Switzerland, 1998
M. Sipper, M. S. Capcarrère, and E. Ronald, A simple cellular automaton that solves the density and ordering problems, International Journal of Modern Physics C, vol. 9, no. 7, pp. 899-902, October 1998
M.Sipper, Computing with cellular automata: Three cases for nonuniformity, Physical Review E, Vol. 57, No. 3, pages 3589-3592, March 1998
A. Stauffer and M. Sipper, On the relationship between cellular automata and L-systems: The self-replication case, Physica D, vol. 116, no. 1-2, pp. 71-80, 1998
M. Sipper, Programming cellular machines by cellular programming, in Bio-Inspired Computing Machines: Toward Novel Computational Architectures, M. Tomassini and D. Mange, Eds., pp. 99-119. Presses Polytechniques et Universitaires Romandes, Lausanne, Switzerland, 1998
M. Sipper, Simple + parallel + local = Cellular computing, in Fifth International Conference on Parallel Problem Solving from Nature (PPSN V), A. E. Eiben, T. Bäck, M. Schoenauer, and H.-P. Schwefel, Eds. 1998, vol. 1498 of Lecture Notes in Computer Science, pp. 653-662, Springer-Verlag, Heidelberg
M. S. Capcarrère, A. G. B. Tettamanzi, M. Tomassini, and M. Sipper, Studying parallel evolutionary algorithms: The cellular programming case, in Fifth International Conference on Parallel Problem Solving from Nature (PPSN V), A. E. Eiben, T. Bäck, M. Schoenauer, and H.-P. Schwefel, Eds. 1998, vol. 1498 of Lecture Notes in Computer Science, pp. 573-582, Springer-Verlag, Heidelberg
M. Sipper, E. Sanchez, D. Mange, M. Tomassini, A. Pérez-Uribe, and A. Stauffer, An introduction to bio-inspired machines, in Bio-Inspired Computing Machines: Toward Novel Computational Architectures, M. Tomassini and D. Mange, Eds., pp. 1-12. Presses Polytechniques et Universitaires Romandes, Lausanne, Switzerland, 1998
A. Stauffer, D. Mange, and M. Sipper, Evolware: Implementing evolving cellular machines using FPGAs, Informatik/Informatique (Journal of the Swiss Society of Computer Scientists), vol. 5, no. 2, pp. 40-42, April 1998
A. Stauffer, M. Sipper, and A. Pérez-Uribe, Some applications of FPGAs in bio-inspired hardware, in Proceedings of 6th IEEE Symposium on FPGAs for Custom Computing Machines (FCCM’98), K. L. Pocek and J. M. Arnold, Eds. 1998, pp. 278-279, IEEE Computer Society, Los Alamitos, California

1997

M. Sipper, If the milieu is reasonable: Lessons from nature on creating life, Journal of Transfigural Mathematics, vol. 3, no. 1, pp. 7-22, 1997
M. Sipper, Evolving uniform and non-uniform cellular automata networks, in Annual Reviews of Computational Physics, D. Stauffer, Ed., vol. V, pp. 243-285. World Scientific, Singapore, 1997
M. Sipper and M. Tomassini, Convergence to uniformity in a cellular automaton via local coevolution, International Journal of Modern Physics C, vol. 8, no. 5, pp. 1013-1024, 1997
M. Sipper, M. Tomassini, and M. S. Capcarrère, Designing cellular automata using a parallel evolutionary algorithm, Nuclear Instruments & Methods in Physics Research, Section A, vol. 389, no. 1-2, pp. 278-283, 1997
M. Sipper, The evolution of parallel cellular machines: Toward evolware, BioSystems, vol. 42, pp. 29-43, 1997
M. Sipper and E. Ruppin, Co-evolving architectures for cellular machines, Physica D, vol. 99, pp. 428-441, 1997
M. Sipper, M. Tomassini, and M. S. Capcarrère, Evolving asynchronous and scalable non-uniform cellular automata, Proceedings of International Conference on Artificial Neural Networks and Genetic Algorithms (ICANNGA97), G. D. Smith, N. C. Steele, and R. F. Albrecht, Eds. 1997, pp. 66-70, Springer-Verlag, Vienna
M. Sipper and M. Tomassini, Evolvable cellular machines, in Proceedings of the Second Conference on Cellular Automata for Research and Industry (ACRI’96), S. Bandini and G. Mauri, Eds. 1997, pp. 177-186, Springer-Verlag, London
M. Sipper, Designing evolware by cellular programming, in Proceedings of The First International Conference on Evolvable Systems: From Biology to Hardware (ICES96), T. Higuchi, M. Iwata, and W. Liu, Eds. 1997, vol. 1259 of Lecture Notes in Computer Science, pp. 81-95, Springer-Verlag, Heidelberg
M. Sipper, D. Mange, and A. Stauffer, Ontogenetic hardware, BioSystems, Vol. 44, No. 3, pages 193-207, 1997
M. Sipper, E. Sanchez, D. Mange, M. Tomassini, A. Pérez-Uribe, and A. Stauffer, A phylogenetic, ontogenetic, and epigenetic view of bio-inspired hardware systems, IEEE Transactions on Evolutionary Computation, vol. 1, no. 1, pp. 83-97, April 1997
M. Sipper, E. Sanchez, D. Mange, M. Tomassini, A. Pérez-Uribe, and A. Stauffer, The POE model of bio-inspired hardware systems: A short introduction, in Genetic Programming 1997: Proceedings of the Second Annual Conference, J. R. Koza, K. Deb, M. Dorigo, D. B. Fogel, M. Garzon, H. Iba, and R. L. Riolo, Eds. 1997, pp. 510-511, Morgan Kaufmann, San Francisco, CA
M. Sipper, M. Goeke, D. Mange, A. Stauffer, E. Sanchez, and M. Tomassini, The firefly machine: Online evolware, in Proceedings of 1997 IEEE International Conference on Evolutionary Computation (ICEC’97), 1997, pp. 181-186
E. Sanchez, D. Mange, M. Sipper, M. Tomassini, A. Pérez-Uribe, and A. Stauffer, Phylogeny, ontogeny, and epigenesis: Three sources of biological inspiration for softening hardware, in Proceedings of The First International Conference on Evolvable Systems: From Biology to Hardware (ICES96), T. Higuchi, M. Iwata, and W. Liu, Eds. 1997, vol. 1259 of Lecture Notes in Computer Science, pp. 35-54, Springer-Verlag, Heidelberg
P. Marchal, P. Nussbaum, C. Piguet, and M. Sipper, Speeding up digital ecologies evolution using a hardware emulator: Preliminary results, in Proceedings of The First International Conference on Evolvable Systems: From Biology to Hardware (ICES96), T. Higuchi, M. Iwata, and W. Liu, Eds. 1997, vol. 1259 of Lecture Notes in Computer Science, pp. 107-124, Springer-Verlag, Heidelberg
M. Goeke, M. Sipper, D. Mange, A. Stauffer, E. Sanchez, and M. Tomassini, Online autonomous evolware, in Proceedings of The First International Conference on Evolvable Systems: From Biology to Hardware (ICES96), T. Higuchi, M. Iwata, and W. Liu, Eds. 1997, vol. 1259 ofLecture Notes in Computer Science, pp. 96-106, Springer-Verlag, Heidelberg

1996

M. S. Capcarrère, M. Sipper, and M. Tomassini, Two-state, r=1 cellular automaton that classifies density, Physical Review Letters, vol. 77, no. 24, pp. 4969-4971, December 1996
M. Sipper, M. Tomassini, and O. Beuret, Studying probabilistic faults in evolved non-uniform cellular automata, International Journal of Modern Physics C, vol. 7, no. 6, pp. 923-939, 1996
M. Sipper and M. Tomassini, Generating parallel random number generators by cellular programming, International Journal of Modern Physics C, vol. 7, no. 2, pp. 181-190, 1996
M. Sipper and M. Tomassini, Co-evolving parallel random number generators, in Parallel Problem Solving from Nature – PPSN IV, H.-M. Voigt, W. Ebeling, I. Rechenberg, and H.-P. Schwefel, Eds. 1996, vol. 1141 of Lecture Notes in Computer Science, pp. 950-959, Springer-Verlag, Heidelberg
M. Sipper and E. Ruppin, Co-evolving cellular architectures by cellular programming, in Proceedings of IEEE Third International Conference on Evolutionary Computation (ICEC’96), 1996, pp. 306-311
M. Sipper, Co-evolving non-uniform cellular automata to perform computations, Physica D, vol. 92, pp. 193-208, 1996
J.-Y. Perrier, M. Sipper, and J. Zahnd, Toward a viable, self-reproducing universal computer, Physica D, vol. 97, pp. 335-352, 1996

1995

M. Sipper, An introduction to artificial life, Explorations in Artificial Life (special issue of AI Expert), pp. 4-8, September 1995, Miller Freeman, San Francisco, CA
M. Sipper, Studying artificial life using a simple, general cellular model, Artificial Life, vol. 2, no. 1, pp. 1-35, 1995, The MIT Press, Cambridge, MA
I. Meilijson, E. Ruppin, and M. Sipper, A single-iteration threshold Hamming network, IEEE Transactions on Neural Networks, vol. 6, no. 1, pp. 261-266, January 1995
M. Sipper, Quasi-uniform computation-universal cellular automata, in ECAL’95: Third European Conference on Artificial Life, F. Morán, A. Moreno, J. J. Merelo, and P. Chacón, Eds., Heidelberg, 1995, vol. 929 of Lecture Notes in Computer Science, pp. 544-554, Springer-Verlag

1994

M. Sipper and Y. Yeshurun, Cost-performance evaluation of analog neural networks and high order networks, Neurocomputing, vol. 6, no. 3, pp. 291-303, 1994
M. Sipper, Non-uniform cellular automata: Evolution in rule space and formation of complex structures, in Artificial Life IV, R. A. Brooks and P. Maes, Eds., Cambridge, Massachusetts, 1994, pp. 394-399, The MIT Press

1993

M. Sipper, A serial complexity measure of neural networks, in IEEE International Conference on Neural Networks, San Francisco, California, March 1993, vol. 2, pp. 962-966

1992

I. Meilijson, E. Ruppin, and M. Sipper, Single-iteration threshold Hamming networks, in NIPS-5: Neural Information Processing Systems 5, S. J. Hanson, J. D. Cowan, and C. L. Giles, Eds. December 1992, pp. 564-571, Morgan Kaufmann Publishers, Inc

1990

M. Sipper and Y. Yeshurun, Pattern classification using teurons, in 10th International Conference on Pattern Recognition, Atlantic City, N.J, June 1990, vol. 1, pp. 433-437, IEEE Computer Society Press