Transcript Lecture 10
CAP6938
Neuroevolution and
Developmental Encoding
Working with NEAT
Dr. Kenneth Stanley
September 27, 2006
Exploiting Speciation
• Keep a list of species with increasing ID’s
• Species elitism: duplicate the species
champs in the next generation
– Only if species is above size 4 or 5
– Irrelevant in rtNEAT
• Stagnation Detection
– Track generations since last improvement for
each species
– Drop fitnesses of stagnant species to near 0
Crossover Issue
• Two different connections can end up
connecting the same nodes
– Maybe disallow
5
9
Look Out for Bugs
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Gene pointing to nodes that aren’t in Gemome
Gene innovation numbers out of order
Node innovation numbers out of order
Duplicate genes
May want to check for these situations after
major operations during debugging
• See Genome::verify() in NEAT C++
• Can check whole population in a loop
Network Activation
• Use standard arbitrary-topology activation
• (Lecture 3)
• Do not activate in layers!
Real-time Evolution
• If all your agents are evaluated simultaneously,
rtNEAT may be more appropriate
• rtNEAT produces and replaces one individual at
a time (no generations)
• See “REAL-TIME NEUROEVOLUTION IN THE
NERO VIDEO GAME ” on my homepage
• Also see NERO
• rtNEAT source available
Your Genes May Have Extra Fields
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Time constants in nodes
Activation function in nodes
Learning parameters in connections
You can have whatever you want, whatever you are
evolving
• Should extra params affect compatibility?
c1 E c2 D
c3W
N
N
• Remember, more fields means more possibilities, but
also more dimensions
Important Methods
• Crossover: mate_multipoint and
mate_multipoint_avg
• Mutation: mutate_add_connection,
mutate_link_weights, mutate_enable_bits,
other?
• Special Genomes Operations: duplicate,
compare (getting the delta for compatibility
distance)
• reproduce (inside Species)
• epoch (inside Population)
• Remember: http://www.freshraisins.com/neatdoc/files/genetics-cpp.html
Developmental Encoding and Nonneural NEAT
• Your genes may not map directly to pieces of
structure
• However, genes can still be marked with
historical markings and complexification can still
occur
• Need a standard starting structure
Sensors Must Be Chosen Wisely
Noisy Evaluation
• Randomness in an environment can cause
evaluation to be inconsistent
• For example, in a game of chance
• Same individual can receive different
fitness on different trials
• Causes confusion for evolution
• Not always fatal, but merits attention
• Maybe give all individuals in same
generation same evaluation sequence
Saving and Loading
/* Species #3 : (Size 5) (AF 6.03094) (Age 29) */
• Genomes/Populations
should be savable and
loadable
• Important for debugging
• Very disappointing to
lose a good thing forever
• Some people use
standards like XML
/* Organism #0 Fitness: 8.77021 Error: 1.03855 */
genomestart 0
trait 1 0.1 0 0 0 0 0 0 0
trait 2 0.2 0 0 0 1 0 0.21903 0
trait 3 0.65 0.110145 0 0 0 0 0 0
node 1 3 1 3
node 2 3 1 1
node 3 3 1 1
node 4 1 0 2
node 9 1 0 0
node 86 1 0 0
gene 3 1 4 -0.798127 0 1 -0.798127 1
gene 3 2 4 3 0 2 3 1
gene 2 3 4 -3 0 3 -3 1
gene 2 3 9 0.505339 0 12 0.505339 1
gene 1 9 4 1.02135 0 13 1.02135 1
gene 1 1 9 -3 0 95 -3 1
gene 1 2 9 2.28649 0 266 2.28649 0
gene 1 2 86 -1.22499 0 281 -1.22499 1
gene 1 86 9 1.72795 0 282 1.72795 1
genomeend 0
/* Organism #1 Fitness: 5.37326 Error: 1.68197 */
genomestart 1
trait 1 0.1 0 0 0 0 0 0 0
trait 2 0.2 0 0 0 1 0 0.21903 0
trait 3 0.65 0.110145 0 0 0 0 0 0
node 1 3 1 3
node 2 3 1 1
node 3 3 1 1
node 4 1 0 2
node 9 1 0 0
Modularity Means Future
Expansion
(and maybe other users)
• Think about what you might want to do someday
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Add new parameters to nodes?
Add new parameters to links?
Change the mapping?
Change platforms?
Completely different experiments?
More visualization?
Change phenotype?
Change genetyoe?
Too Much Scope = Too Much Rope
• Go for proof of concept
• What feature matters least?
• If nothing works what could be a
prerequisite task?
• Incremental evolution strategies
Next Class:
Developmental Encoding
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The power of reuse
Prior work
Biological underpinnings
The future
A Taxonomy for Artificial Embryogeny by Kenneth O. Stanley and Risto Miikkulainen
(2003)