Transcript The Role of Artificial Life, Cellular Automata and

The Role of Artificial Life, Cellular
Automata and Emergence in the
study of Artificial Intelligence
Ognen Spiroski
CITY Liberal Studies
2005
Presentation Outline
• Artificial Intelligence and Artificial Life
• Complex Systems and Artificial Life
– Emergence
– Self-organization and the edge of chaos
• The Digital Worlds of Artificial Life
• Cellular Automata
– Conway’s Game of Life
Artificial Intelligence and
Artificial Life
• Definition of AI
– AI is the study of the mechanisms underlying
intelligent behaviour through the construction
and evaluation of artifacts that attempt to
enact those mechanisms
• Classic AI
– Logic based, symbol manipulating
– Top-down models simulate intelligent
behaviour
Artificial Intelligence and
Artificial Life (cont’d)
• Behaviour-oriented AI
– Inspired by biology
• “defines intelligence in terms of observed
behaviour and self-preservation. It is based on the
idea that the essence of biological systems is their
capacity to continuously preserve and adapt
themselves”
– Bottom-up computational models result in
emergent behaviour
Artificial Intelligence and
Artificial Life (cont’d)
• Behaviour-oriented AI paradigms
•
•
•
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Connectionist
Evolutionary
Agent-based
Emergent
– Don’t rely on a central scheme which explicitly
describes the intelligent behaviour
– Through the interactions of many simple
structures, complex behaviour that is not
directly programmed is exhibited
Defining Artificial Life
• Definition
– the analysis and study of life and life-like
processes in man-made systems through the
use of simulation and synthesis
• Why?
– Broaden understanding of what life is by
building it artificially
– Explore synthetic evolution
– Life-as-it-could-be vs Life-as-we-know-it
Defining Life
• The problem of defining what life “is”
• Life is built by simple, non-living components
• Yet it appears to be more than the mere sum of
their interaction
• Traditional definitions
– Test for certain properties:
• Metabolism, adaptability, self-maintenance,
autonomy, growth, replicability, evolution, etc.
– Incomplete
Defining Life – Complex Systems
• Complex Systems
– Life is found in complex dynamic systems
– Life requires a certain level of complexity in a
dynamic system
• Defining the threshold of complexity which
separates living from non-living systems
• Life - an emergent phenomenon in a
complex system
Emergence
• Defining emergence
– “The theory of emergence involves three propositions:
• (1) that there are levels of existence . . .
• (2) that there are marks which distinguish these levels from
one another . . .
• (3) that it is impossible to deduce marks of a higher level
from those of a lower level . . . ”
– To define life as an emergent phenomenon implies
the acknowledgement that different properties of
systems require different, qualitatively unrelated,
epistemological categories and models, which cannot
be reduced to the properties of the component parts
of the system.
Artificial Life and Emergence
• Search for the origin of life
– The threshold of complexity needed for the
emergence of life
• Understand life through computational
emergence
Self-organization
• A hallmark of emergence
• Definition
• the spontaneous formation of well organized
structures, patterns, or behaviors, from random
initial conditions
• Found in complex dynamical systems
• these systems tend to reach a particular state, or a
set of cycling states, or a small volume of their
state space, with no external interference. All the
mechanisms dictating its behavior are internal to
the system: self-organization as opposed to
externally imposed organization
The Edge of Chaos
• Ordered systems
– Not enough complexity
for life to emerge
• Chaotic systems
– Too rapid changing to
self-organize sufficient
complexity and sustain
life
• Complex systems
– Life is found at the
edge of chaos
(Langton)
Phases found in dynamical systems
The Digital Worlds of Artificial Life
• Christopher G. Langton:
• "The principle assumption made in Artificial Life is
that the 'logical form' of an organism can be
separated from its material basis of construction,
and that 'aliveness' will be found to be a property
of the former, not of the latter.“
• Life in a logical informational universe
The Digital Worlds of Artificial Life
• Simulations in the digital medium
– Ease of research
• Well known formal structure
• Data gathering
• Completely repeatable experiments
– Fast
• Is it “real life”?
Cellular Automata
• Definition
– “A cellular automaton is a discrete dynamical system.
Space, time, and the states of the system are
discrete. Each point in a regular spatial lattice, called
a cell, can have any one of a finite number of states.
The states of the cells in the lattice are updated
according to a local rule. That is, the state of a cell at
a given time depends only on its own state one time
step previously, and the states of its nearby neighbors
at the previous time step. All cells on the lattice are
updated synchronously. Thus the state of the entire
lattice advances in discrete time steps. “
• An example of complex systems
Cellular Automata History
• History
– von Neumann and self-reproducing automata
– Conway’s “Game of Life”
– Wolfram – the Universe as a CA
The Game of Life
• Invented by
mathematician John
Conway
• The best known
example of a CA
– Very simple, yet
– An excellent example
of emergence and
self-organization
Game of Life - Definition
• A two-state two-dimensional CA with three
very simple rules of action:
1. One inactive cell surrounded by three active cells
becomes active ("it's born")
2. One active cell surrounded by 2 or 3 active cells
remains active
3. In any other case, the cell "dies" or remains
inactive.
Game of Life - Examples
• Still life objects (block, beehive, boat, ship, loaf)
• They simply remain the same in the next generation
• Oscillators
• They change throughout generations, but essentially cycle
through the same pattern
• Gliders
• They move diagonally across the grid
• The Queen Bee Shuttle
• Spaceships
• They move left, right, up or down instead of on diagonals like
gliders
…
Game of Life - Research
• A completely known universe
• Computation is possible
– A Turing machine has been implemented
– Formal proof that self-reproducing
mechanisms are possible
…
Summary
• Artificial Life:
– Biology inspired
– Multidisciplinary approach
– Computational evolution
• Complex Systems
– Emergence and self-organization
– Life at the edge of chaos
• Cellular Automata
– Simple, yet effective models for studies in Artificial
Life