Informace k semináři Evolving structures in mathematics NMMB471
Výběrový seminář pro
studenty bakalářského, navazujícího magisterského a doktorského studia
Tvůrčí seminář o možnostech, jak modelovat evoluci
složitých adaptujících se systémů na
počítači
Seminář vede
Tomáš Mikolov za pomoci Jiřího Tůmy a případných hostů
Místo a čas
Seminární místnost katedry algebry, 3. patro, budova Sokolovská 83, úterý 15,40
Konzultace
Lze domluvit osobně po semináři nebo mailem na tuma (at) karlin.mff.cuni.cz, nebo telefonem 2 2191 3240
Zápočet
Bude za pravidelnou a aktivní účast na semináři
Program semináře v tomto semestru
25.2.2020 Tomáš Mikolov, prezentace
3.3.2020 Bára Hudcová, Komplexní systémy, klasifikace pomocí tranzient, prezentace
10.3.2020 Hugo Cisneros, Evaluating complexity in cellular automata, prezentace
Zde je loňský plánovaný program semináře, na tento rok bude ještě upraveno.
- We will discuss some early ideas about
artificial intelligence, and high-level
overview of topics such as
Turing-completeness.
- In this book, Marwin advocates that
complex intelligent behavior is a result of
cooperation of simple agents, and that the
human mind can be explained this way.
- Occam's razor, Minimum description
length, Kolmogorov complexity, Algorithmic
probability, measures of complexity proposed
by Gell-Mann
- parallel string rewriting grammars that
can generate objects that resemble those found
in nature (leaves, trees); the grammars can be
very trivial, while the objects may appear
complex to us
Fractals: The fractal geometry of nature,
B. Mandelbrot
- Fractals are objects that appear the same
at different scales, while some appear rather
complex to us.
- Conway's Game of Life can be seen as a
simple example how cellular automatons work.
However, the ideas here are deeper than they
appear at first, and we can see that the
original motivation for the development of
cellular automatons was to design
mathematical structures that can copy
themselves in a non-trivial way, and
possibly increase in complexity while doing
so.
- Deals with mathematical structures that
can have similar properties to how we define
life: self-reproduction, evolution.
Genetic Algorithms, J. Holland
- We will discuss the basic ideas behind
evolutionary and genetic algorithms and
genetic programming, and compare these
algorithms with the previously discussed
attempts to design objects that can evolve.
Neuroevolution
- Evolving neural networks through
augmenting topologies, K. O. Stanley and
R. Miikkulainen