General information:
Code:
UBPJO-270
Name:
Introduction to Artificial Life
Profile of education:
Academic (A)
Lecture language:
English
Responsible teacher:
dr inż. Pomorski Krzysztof (kdvpomorski@kt.agh.edu.pl)
Academic teachers:
dr inż. Pomorski Krzysztof (kdvpomorski@kt.agh.edu.pl)
Module summary

We aim to find bases for holistic view of the world around us with possible minimal number of necessary assumptions and with minimal number of simplifications.

Description of learning outcomes for module
MLO code Student after module completion has the knowledge/ knows how to/is able to Connections with FLO Method of learning outcomes verification (form of completion)
Social competence
M_K001 Connection between science and humanistic fields will be developed. This allows to conduct concrete discussions based on well predefined assumptions.
Skills
M_U001 The basic ability in conducting analysis of given problem from Artificial Life and mapping it into basic ingredients of mathematical objects is expected to take place during the course.
Knowledge
M_W001 Basic knowledge of theory of complex systems, cellular automat, agent modeling, neural networks and finite state automata in the context of biology, robotics and sociology. The ability to distinguish between Artifcial Intelligence and Artificial Life is assumed to be acquired during the course. Activity during classes
M_W002 Knowledge of basic concepts in Synthetic psychology is expected outcome of the course. Case study
FLO matrix in relation to forms of classes
MLO code Student after module completion has the knowledge/ knows how to/is able to Form of classes
Lecture
Audit. classes
Lab. classes
Project classes
Conv. seminar
Seminar classes
Pract. classes
Zaj. terenowe
Zaj. warsztatowe
Others
E-learning
Social competence
M_K001 Connection between science and humanistic fields will be developed. This allows to conduct concrete discussions based on well predefined assumptions. + - + - - - - - - - -
Skills
M_U001 The basic ability in conducting analysis of given problem from Artificial Life and mapping it into basic ingredients of mathematical objects is expected to take place during the course. + - + - - - - - - - -
Knowledge
M_W001 Basic knowledge of theory of complex systems, cellular automat, agent modeling, neural networks and finite state automata in the context of biology, robotics and sociology. The ability to distinguish between Artifcial Intelligence and Artificial Life is assumed to be acquired during the course. + - + - - - - - - - -
M_W002 Knowledge of basic concepts in Synthetic psychology is expected outcome of the course. - - + - - - - - - - -
Module content
Lectures:
13 theoretical topics is defining the approach towards Artificial Life

I. An attempt to define the life and motivation of interest in Alife (1h):
→ biological systems
→ mechanical works
→ humanoid robots
→ virtual reality
→ mind in the vessel
II. A humanistic definition of natural and artificial intelligence (1h).
III. The laws of physics and the variety of dynamical systems (2h):
→ Newton’s law
→ Schrodinger equation
→ outline of classical and quantum mechanics
→ a brief overview of dynamic systems
→ an outline of theoretical mechanics and electromagnetism
→ chaotic behavior and harmonic motion on the pendulum
→ occurrence of order and thermodynamic principles
→ determinism and stochasticity, the concept of entropy and information
V. The concept of the algorithm and the Turing machine (1h).
VI. The concept of a finite state machine (1h):
→ Conway’s game of life
→ Anticipation algorithms
VII. Neural networks and the concept of natural and artificial evolution and the concept
genetic algorithm (1h).
VIII. Braitenber vehicles and an experiment in synthetic psychology (1h).
→ basic Braitenberg vehicles
→ generalized Braitenberg vehicles with a neural network
IX. The concept of cognitive system and embodied artificial intelligence (2h)
→ the concept of social force [social force concept]
→ passive walker as an example of a non-cognitive physical system
→ symbol grounding problem
→ ecological niche
→ morphological computation
→ the difference between classic AI and embodied AI
→ co-evolution of the motor, sensory and decision-making systems
→ the concept of emergence
X. Theory of games (1h):
→ The Prisoner’s Dilemma game
→ Nash balance
→ The relationship between game theory and neural networks and a finite state machine
→ Ethics as a derivative of the chosen strategy
→ Cognitive Pre-predator model and game theory
XI. Artificial chemistry and the concept of programmable matter (1h).
→ cell division described by a finite state machine
XII. Developing and expanding the universal model of reality (2h):
→ Human-computer interface and human interaction with robots
→ personality identification on the example of facebook profiles
→ digitization of history and economics on the example of Civilization and Conquest,
→ experiment utopia mouse (https://pl.wikipedia.org/wiki/Eksperyment_Calhouna)
→ looking for links between human perception, ideology and religion
→ searching for a robotic definition of philosophy and culture
XIII. Philosophy, development trends Artficial Life, Artificial Life Art (1h).
→ ALIFE definition according to Langton
→ challenges for philosophy
→ challenges for the technology branch
→ challenges for sociology
→ dilemma of interdisciplinarity and incompatibility of the approach of various disciplines
→ methodological differences between the humanities and fundamental sciences

Laboratory classes:
13 topics of Artificial Life course

I. An attempt to define the life and motivation of interest in Alife:
→ biological systems
→ mechanical works
→ humanoid robots
→ virtual reality
→ mind in the vessel
II. A humanistic definition of natural and artificial intelligence.
III. The laws of physics and the variety of dynamical systems:
→ Newton’s law
→ Schrodinger equation
→ outline of classical and quantum mechanics
→ a brief overview of dynamic systems
→ an outline of theoretical mechanics and electromagnetism
→ chaotic behavior and harmonic motion on the pendulum
→ occurrence of order and thermodynamic principles
→ determinism and stochastic models, the concept of entropy and information
V. The concept of the algorithm and the Turing machine.
VI. The concept of a finite state machine:
→ Conway’s game of life
→ Anticipation algorithms
VII. Neural networks and the concept of natural and artificial evolution and the concept
genetic algorithm.
VIII. Braitenber vehicles and an experiment in synthetic psychology.
→ basic Braitenberg vehicles
→ generalized Braitenberg vehicles with a neural network
IX. The concept of cognitive system and embodied artificial intelligence
→ the concept of social force [social force concept]
→ passive walker as an example of a non-cognitive physical system
→ symbol grounding problem
→ ecological niche
→ morphological computation
→ the difference between classic AI and embodied AI
→ co-evolution of the motor, sensory and decision-making systems
→ the concept of emergence
X. Theory of games:
→ The Prisoner’s Dilemma game
→ Nash balance
→ The relationship between game theory and neural networks and a finite state machine
→ Ethics as a derivative of the chosen strategy
→ Cognitive Pre-predator model and game theory
XI. Artificial chemistry and the concept of programmable matter.
→ cell division described by a finite state machine
XII. Developing and expanding the universal model of reality:
→ Human-computer interface and human interaction with robots
→ personality identification on the example of facebook profiles
→ digitization of history and economics on the example of Civilization and Conquest,
→ experiment utopia mouse (https://pl.wikipedia.org/wiki/Eksperyment_Calhouna)
→ looking for links between human perception, ideology and religion
→ searching for a robotic definition of philosophy and culture
XIII. Philosophy, development trends Artficial Life, Artificial Life Art.
→ ALIFE definition according to Langton
→ challenges for philosophy
→ challenges for the technology branch
→ challenges for sociology
→ dilemma of interdisciplinarity and incompatibility of the approach of various disciplines
→ methodological differences between the humanities and fundamental sciences

Student workload (ECTS credits balance)
Student activity form Student workload
Summary student workload 150 h
Module ECTS credits 6 ECTS
Completion of a project 150 h
Additional information
Method of calculating the final grade:

20 percent of points can be obtained by active discussion with good arguments and examples or by student presentation.

40 percent of points are due to accomplishment of course main report on given subject that is related to Artificial Life discipline and determined by the consultation with the lecturer.

40 percent of points are due to written exam in the middle of semester.

Prerequisites and additional requirements:

1. Knowledge of Mathematics at the level of High School.
2. Knowledge of Physics at the Level of High School.
3. Basic knowledge of Philosophy.
4. Basic knowledge of theory of algorithms (it is not compulsory but is highly welcome).

Recommended literature and teaching resources:

0. www.alife.org, 2018.alife.org, https://mitpress.mit.edu/books/artificial-life-13,
http://www.biota.org/, http://alife13.org/wp-content/uploads/2012/07/ALife13Program.pdf
2. https://mitpress.mit.edu/books/animals-animats-6
3. http://sacral.c.u-tokyo.ac.jp/publication.html
4. Rofl Pfeiffer, Information processing via physical soft body, Nature 2015
https://www.nature.com/articles/srep10487
5. Self-Organization, Embodiment, and Biologically Inspired Robotics, Rolf Pfeifer, Max
Lungarella, Fumiya Iida, Science 2007,
http://science.sciencemag.org/content/318/5853/1088/tabfigures-data
6. The quest for AI: a history of ideas and achievements, Cambridge University Press,
http://www.cambridge.org/us/0521122937, Nils J. Nilsson, Stanford University
7. H. G. Schuster and W. Just, Deterministic Chaos
8. Roger Penrose, Nowy umysł cesarza: O komputerach, umysłach i prawach fizyki
9. Braitenberg, V. (1984). Vehicles: Experiments in synthetic psychology. Cambridge, MA: MIT
Press
8. Training Deep Spiking Neural Networks using Backpropagation,
9. https://en.wikipedia.org/wiki/Lotka%E2%80%93Volterra_equations , Prey-predator model
10. Passive walker, http://www-personal.umich.edu/~artkuo/Passive_Walk/passive_walking.html
11. Lectures on neural networks, https://uvadlc.github.io/lectures/lecture1.pdf
12. http://www.cyberryba.pl/
13. Stanisław Lem mówi o nauce i wierze, https://www.youtube.com/watch?v=pm0VXfxlQlk
14. Private traits and attributes are predictable from digital records of human behavior
Michal Kosinskia, David Stillwella and Thore Graepel
http://www.pnas.org/content/110/15/5802.full
15. https://pl.wikipedia.org/wiki/Eksperyment_Calhouna
16. Science Fiction, Artificial Life and Posthumanism., Westhoek, M. (2011) Faculty of
Humanities Theses (Bachelor thesis)
17. https://arxiv.org/pdf/nlin/0310041.pdf , Generalization of Braitenberg vehicles
18. Artificial Life. 2015 Summer;21(3):261-70. doi: 10.1162/ARTL_e_00166,
Artificial Life Art, Creativity, and Techno-hybridization (editor’s introduction), Dorin A
19. Takashi Ikegami: The case for complexity over simplicity in science , TED Talk,
https://www.youtube.com/watch?v=tOLIHhjNlBc
http://archive.tedxtokyo.com/en/talk/takashi-ikegami/
20. http://www.shanghailectures.org/ , Shanghai AI lectures
21. Studies in History and Philosophy of Biological and Biomedical Sciences 44 (2013) 688–696,
Is the creation of artificial life morally significant?, Thomas Douglas, Russell Powell, Julian
Savulescu
22.Artificial Life as Philosophy, Daniel C. Dennett:
https://ase.tufts.edu/cogstud/dennett/papers/alifephl.htm
23. Tatarkiewicz, History of Philosophy
24. Mind Time Machine, https://vimeo.com/28762095
25. Introduction to genetic algorithms,
https://www.doc.ic.ac.uk/~nd/surprise_96/journal/vol1/hmw/article1.html
26. An introduction to econophysics, Correlations and Complexity in Finance
Rosario Mantenga. H.Eugene Stanley
27. Entropy in Artificial Life,
http://www.science20.com/open_archives/blog/entropy_and_artificial_life-75373
28. Advanced course on Artificial Life, http://www.springer.com/gp/book/9781461272311
29. Entropy and biology, http://www.panspermia.org/seconlaw.htm
30. Prisoner dilemma, http://www.econlib.org/library/Enc/PrisonersDilemma.html

Scientific publications of module course instructors related to the topic of the module:

. P.Prokopow, K.Pomorski, Simulation study of the importance of biarticular muscles on human vertical jump performance, International Journal of Experimental and Computational Biomechanics, Vol.1, Issue 4, 2011.

. P.Prokopow, S.Szyniszewski, K.Pomorski, The effects of changes in the timing of muscle activation on jump height: a simulation study, 2005 .

. P.Tempczyk, P.Prokopow, Transport properties of a multi-pendulum system,
De la societe des sciences et des lettres des Lodz 62, 103, 2012.

Additional information:

It is highly recommendable to refer to the following publications as give by Webpage:
http://sacral.c.u-tokyo.ac.jp/publication.html
and to the publication:
“Life as an emergent phenomenon: Studies from a large-scale boid simulation and web data
Article in Philosophical Transactions of The Royal Society A Mathematical Physical and Engineering” Sciences 375(2109):20160351 · December 2017
(https://www.researchgate.net/publicatio/321053223_Life_as_an_emergent_phenomenon_Studies_from_a_large-scale_boid_simulation_and_web_data) .

During classes it is recommendable to analyse projects described by Webpage:
http://sacral.c.u-tokyo.ac.jp/project.html .

. Prezentacjach:
Takashi Ikegami: The case for complexity over simplicity in science
(https://www.youtube.com/watch?v=tOLIHhjNlBc)