2001 Complex Systems Summer School Budapest-Readings

2001 Complex Systems Summer School Budapest Home Faculty Participants Readings

School Bibliography:

Abarbanel, H. Analysis of observed chaotic data.
Adami, Christoph. Introduction to artificial life.
Axler, Sheldon. Linear algebra done right.
Bar-Yam, Yaneer. Dynamics of complex systems.
Belew, R.K. and M. Mitchell. Adaptive individuals in evolving populations: models and algorithms.
Bonabeau et al, Swarm intelligence.
Bouwmeester, Dirk, Artur Ekert and Anton Zeilinger. The physics of quantum information: quantum cryptography, quantum teleportation, quantum computation.
Brooks, R.A. and P. Maes. Artificial life IV.
Campbell, D., R. Ecke and J. Hyman. Nonlinear science: the next decade.
Cover, Thomas M. and Joy A. Thomas. Elements of information theory.
Cowan, G., D. Pines and D. Melzner. Complexity: metaphors, models and reality.
Cramer, Harold. Mathematical methods of statistics.
Cvitanovic, P. Universality in chaos.
Czaran, T. Spatiotemporal models of population and community dynamics.
Davis, L.D. The handbook of genetic algorithms.
Dieckmann, U., R. Law and J.A.J. Metz eds. The geometry of ecological interactions.
Feller. An introduction to probability theory and its applications.
Finney, Ross L., and Donald R. Ostberg. Elementary differential equations with linear algebra.
Fogel, D.B. Evolutionary computation: toward a new philosophy of machine intelligence.
Forrest, S. Emergent computation.
Goldberg, D.E. Genetic algorithms in search, optimization, and machine learning.
Gonick, Larry and Wollcoot Smith. The cartoon guide to statistics.
Grimmett, G.R. and D. R. Stirzaker, Probability and random processes.
Hamming, R. W. Coding and information theory.
Holland. Adaptation in natural and artificial systems.
Holland. Emergence.
Holland. Hidden Order.
Hopcroft, J.E. and J. D. Ullman, Introduction to automata theory, languages and computation.
Kauffman. Origins of Order.
Kemeny, J.G. and J. L. Snell. Finite Markov.
Kihong and Willinger. Self-similar network traffic and performance evaluation.
Langton, C.G. Artificial life: an overview.
Langton, C.G. et al, eds. Artificial life II & III.
Langton, C.G. and K. Shimohara, eds. Artificial life V.
Mayo, Deborah G. Error and the growth of experimental knowledge.
McClelland, J.L. and D. E. Rumelhart. Explorations in PDP.
Mitchell. An introduction to genetic algorithms.
Mitchell, Tom. Machine Learning.
Morowitz. Beginnings of cellular life : Metabolism recapitulates biogenesis.
Nelson, David L. and Michael M. Cox. Lehninger principles of biochemistry.
Newman and Barkema. Monte Carlo methods in statistical physics.
Nielsen, Michael A. and Isaac L. Chuang, Quantum computation and quantum information.
Nijhout, Nadel, and Stein. Pattern formation in the physical and biological sciences.
Ott, E., T. Sauer and J. Yorke. Coping with chaos.
Paun, G., G. Rozenberg and A. Salomaa. DNA computing: new computing paradigms.
Papadimitriou, Christos H. Computational complexity.
Pierce, John R. An introduction to information theory: symbols, signals and noise.
Pliscke and Bergersen. Equilibrium statistical physics.
Schroeder, Manfred. Fractals, chaos, power laws, minutes from an infinite paradise.
Shannon and Weaver. The Mathematical theory of communication.
Siegelmann, Hava T. Neural networks and analog computation: beyond the Turing limit.
Smith, J Maynard and E. Szathmary. The major transitions in evolution.
Smith, J Maynard and E. Szathmary. The origins of life.
Sornette, D. Critical phenomena in natural sciences.
Strang, Gilbert. Linear algebra and its applications.
Strogatz, S. Nonlinear dynamics and chaos.
Vicsek, Tamas, Fractal growth phenomena.
Weigend, A.S. and N. S. Gershenfeld. Time series prediction: forecasting the future and understanding the past.
Wolfram. Theory and applications of cellular automata.
Zurek, Complexity, entropy, and the physics of information.