Nota Importante: Questo pagina è strettamente legata a PROBABILITA’, CAOS E FRATTALI nelle liste di letture consigliate in Matematica, vanno quindi consultate insieme.
John Holland - Complexity Very short introduction
Melanie Mitchell - Complexity. A Guided Tour
M. Mitchell Waldrop - Complexity. The Emerging Science at the Edge of Order and Chaos
Simon Levin - Fragile Dominion. Complexity And The Commons
Albert-laszlo Barabasi - Linked: How Everything Is Connected to Everything Else
trad.it. “Link”
Steven H. Strogatz - SYNC The Emerging Science of Spontaneous Order
Geoffrey West - Scale: The Universal Laws of Life, Growth, and Death in Organisms, Cities, and Companies
Duncan J. Watts - Small Worlds: The Dynamics of Networks Between Order and Randomness (2004)
Duncan J. Watts - Six Degrees: The Science of a Connected Age
Guido Caldarelli, Michele Catanzaro - Networks. A very short introduction (2012)
trad.it. Scienza delle reti
A. Vespignani - L’algoritmo e l’oracolo: come la scienza predice il futuro e ci aiuta a cambiarlo
Giorgio Parisi - Come in un volo di storni
James Ladyman, Karoline Wiesner - What is a Complex System? (2020)
Hiroki Sayama - Introduction to the Modeling and Analysis of Complex Systems-Open SUNY Textbooks
Stefan Thurner, Rudolf Hanel, Peter Klimek - Introduction to the Theory of Complex SystemsP (2018)
Sergey Dorogovtsev - Lectures on Complex Networks
Mark Newman, Duncan J. Watts, Albert-László Barabási - The Structure and Dynamics of Networks (2013)
Guido Caldarelli -Scale-Free Networks: Complex Webs in Nature and Technology (2013)
Alain Barrat, Marc Barthélemy, Alessandro Vespignani - Dynamical Processes on Complex Networks
Allen Downey - Think Complexity (2nd ed.)
Herbert Simon - The Science of the Artificial
Risorse Online:
Brunello Tirozzi - Modelli Matematici di Reti Neurali - Padova, 1995
D.J.C. Mac Kay - Information Theory, Inference and Learning Algorithms
C.M. Bishop - Pattern Recognition and Machine Learning
Mehta et al. - A high-bias, low-variance introduction to Machine Learning for physicists
A.C.C. Coolen, R. Kuhn, P. Sollich - Theory of Neural Information Processing Systems
Simon O. Haykin - Neural Networks and Learning Machines
I. Goodfellow, Y. Bengio, A. Courville - Deep Learning
A. Geron - Hands-On Machine Learning With Scikit-Learn and Tensorflow