Artificial life, or A-life, studies artificial systems that mimic natural living systems through computer simulation, robotics, and synthetic biology. It aims to understand the general principles of life in any context. Key areas of A-life research include software-based simulations using cellular automata and neural networks, hardware-based robotics, and biochemical simulations of synthetic DNA. Open problems in A-life include understanding the origin of life and the potentials and limits of living systems.

1. Artificiel Life « A-
Life »
PRESENTED BY
ABBAS YOUSSOUF
DJAMEI MOHAMED ZINEDDINE
FACULTY SIENCE AND TECHNOLOGY
DEPERTEMANT INFORMATIQUE
SOFTWARE ENGINEERING AND DISTRIBUTED SYSTEM

2. Plan
A-life
A-life based
Exemples
Open problems
Conclusion

3. ALife
DEFENITION :
Artificial life as a is a field of study, hosting experts from computer science,
biology, physics, chemistry, and mathematics, as well as philosophers and
artists , studies artificial systems mimicking some features of living systems
and their processes.
There are three kinds of alife : soft , hard ,wet

4. A-life
The Origin
The phrase ‘artificial life’ was coined by Christopher Langton, who envisioned a study of life as
it could be in any possible setting in 1986 ,
Christopher Langton 1949
American
computer scientist
and theoretical biologist

5. A-life
Organizations
International Society of Artificial Life
ISAL is a "democratic, international, professional society dedicated to promoting scientific
research and education relating to artificial life, including sponsoring conferences,
publishing scientific journals and newsletters, and maintaining web sites related to
artificial life",[originally incorporated in 2001
Grey Thumb Society
The Grey Thumb Society was a group of "scientists, engineers, hackers, artists, and
hobbyists... with a strong interest in artificial life, artificial intelligence, biology, complex
systems, and other related topics". Grey Thumb societies appeared around the world but
by 2011 most of the groups' activities had wound down.

6. A-life based
Philosophy
The modeling philosophy of artificial life strongly differs from traditional modeling
by studying not only "life-as-we-know-it" but also "life-as-it-might-be"
Artificial life research is not limited to life forms existing on the Earth. It rather
attempts to study the general principles of life which are common to all instances of
life, both already recognized and yet unknown.

7. A-life based
1Software-based ("soft")
Techniques
 Cellular automata
Alife and cellular automata share a closely tied history. ( game of life example code
sources)
Artificial neural networks are sometimes used to model the brain of an agent. Although
traditionally more of an artificial intelligence technique, neural nets can be important for
simulating population dynamics of organisms that can learn.

8. A-life based
Notable simulators
This is a list of artificial life/digital organism simulators examples :
Sumilator driven by started
AVIDA executable DNA 1993
FRAMASTICKS executable DNA 1996
Geb neural net
1997

9. A-life based
Hardware-based ("hard")
Hardware-based artificial life mainly consist of robots, that
is, automatically guided machines able to do tasks on their own.
Stiquito 1992

10. A-life based
Biochemical-based ("wet")
Biochemical-based life is studied in the field of synthetic biology. It involves e.g. the creation
of synthetic DNA. The term "wet" is an extension of the term "wetware"

11. Game of life (Conway’s Game)
The Game of Life, also known simply as Life, is a cellular automaton devised by the
British mathematician John Horton Conway in 1970.
The game is a zero-player game, meaning that its evolution is determined by its initial state,
requiring no further input. One interacts with the Game of Life by creating an initial
configuration and observing how it evolves, or, for advanced players, by creating patterns with
particular properties

12. Cells in a rectangular grid (infinite, with zero boundary conditions).
• Each cell is either living or dead.
• The state of the cell depends on its previous state and on the states of the
surrounding cells .
• The state of all cells changes synchronously (all at once).
• All cells are controlled by the same rules:
1. A living cell with less than 2 living neighbors dies (insufficient inhabitation).
2. A living cell with more than 3 living neighbors dies (starvation).
3. A living cell with 2 or 3 neighbors survives.
4. A dead cell with exactly 3 neighbors revives.
• The rules can be simplified: a cell is alive in the next generation if
1. it has 3 living neighbors, or
2. it is alive and has 2 living neighbors.
• The behavior of the whole system depends on the initial pattern only!

14. Open problems
oHow does life arise from the nonliving?
oWhat are the potentials and limits of living systems?
oHow is life related to mind, machines, and culture?

15. Conclusion
 Artificial life studies the laws and phenomena taking place in real
living systems.
The basic research tool is simulation.
 Goals:
 Understand the effects of simple rules in complex systems.
 Take advantage of these (maybe modified) principles to solve
practical tasks.

16. E.G sources code
the Game of life
Framasticks simulator

17. Questions ??
Thanks for your attentions