Using Evolutionary Computation
as a Creativity
-
Support Tool
Tim Chabuk
University of Maryland
Jason Lohn
Carnegie Mellon University
Derek Linden
X5 Systems
Jim Reggia
University of Maryland
NSF CreativeIT Workshop, January 2009
Pilot
Example: Self
-
Replicating Machines
•
artificial structures/systems that produce copy of themselves
•
why study?
-
insight into biological replication
-
understanding origins of life
-
understanding principles/algorithms
-
potential applications
•
•
•
A B
B
C
t
t
+1
•
historically, most work done with
cellular automata
•
discrete space of cells, discrete time
•
local, parallel computations
Rule set:
A . B C .
B
etc.
Game of Life
Two Primary Classes of Replicators
tape
Tape
control
Construction
control
Construction
arm
Replica
under
construction
John von Neumann (1950’s)
-
29 state cells
-
universal constructor computer
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complicated
(~100k cells, 100k rules)
Chris Langton (1980’s)
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8 state cells
-
self
-
replicating loop
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simpler, implemented
Replication of Loop
t = 80
t = 115
t = 150
t = 6
t = 3
search for simplest, emergence from “primordial soup”,
simultaneous tasks, etc.
A Half Century of Cellular Replicators
•
hand
-
crafted rule sets
•
restricted to these two broad classes
Pan Z, Reggia J, Gao D. Properties of Self
-
Replicating Cellular
Automata Systems Discovered Using Genetic Programming,
Advances in Complex Systems
, 10 (Suppl. 1), 2007, 61
-
84.
Question:
Is automated discovery of novel self
-
replicating structures possible?
Approach:
-
given an arbitrary initial configuration
-
use genetic programming to evolve needed rules
Evolved Replicators
initial structure
evolved rule tree
GP ran quickly on standard PC but how
do the resulting replicators work?
Resulting Replicator Behavior
•
growth, separation of replicants
•
fastest CA replicant ever reported
t
= 2
t
= 1
t
= 0
Another Initial Structure
debris
larger,
repetitive
components
whole new family
of self
-
replicating
configurations
Other Structures?
Evolves same rule table as that
created previously by people?
Replicator Factory:
-
creates rules for arbitrary configurations to replicate
-
rule sets are parsimonious and fast
-
novel replication process
relative to past manual approaches
-
used to study properties of replicators
Pilot: Causally
-
Guided Evolutionary Creativity
•
causality
in human creativity
•
Goal:
guide EC in part using problem specific causal relations
•
Process:
1. specify problem
-
specific causal relations
2. integrate causal influences on evolutionary process
3. validate approach
•
Progress to date:
-
antenna array design as target task
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derivation of causal relations
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causal reasoning algorithm
-
integrated with evolutionary process
-
initial experimentation
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