Evolutionary Robotics Tutorial
Josh Bongard
Director of the Morphology, Evolution and Cognition LaboratoryDepartment of Computer ScienceVermont Complex Systems CenterVermont Advanced Computing Core
University of Vermont
July 30, 2014
www.reddit.com/r/ludobotswww.uvm.edu/∼mwagy/robots/dotbot/
Boston Dynamics: Big Dog (2005)
Boston Dynamics: Cheetah (2012)
Raffaello D’Andrea’s Quadcopters (2013)
Marc Raibert’s 3D Biped (?)
Marc Raibert’s 3D Biped (1992)
Why Make Robots?
Evolutionary Robotics
Bongard & Pfeifer, 2002, Bongard, Zykov & Lipson, 2006,Procs of the 7th Intl Conf on the Sim of Adapt Beh Science
Why Make Robots?
Different approaches to understanding life/intelligence
Braitenberg Vehicles 2a and 2b
Braitenberg Vehicle 3
?
Evolution of Artificial Neural NetworksCircles=neurons; arrows=synaptic connections
sensor neurons
interneurons
motor neuronsm1m2 mp
i1 i2 in
s1 s2 sm
network 1
fitness: 2.3 meters
Generation 1
Evolution of Artificial Neural NetworksCircles=neurons; arrows=synaptic connections
m1m2 mp
i1 i2 in
s1 s2 sm
m1m2 mp
i1 i2 in
s1 s2 sm
network 1
network n
fitness: 2.3 meters
fitness: 2.8 meters
Generation 1
Evolution of Artificial Neural NetworksCircles=neurons; arrows=synaptic connections
m1m2 mp
i1 i2 in
s1 s2 sm
m1m2 mp
i1 i2 in
s1 s2 sm
network 1
network n
fitness: 2.3 meters
fitness: 2.8 meters
Generation 1
m1m2 mp
i1 i2 in
s1 s2 sm
m1m2 mp
i1 i2 in
s1 s2 sm
network n1
network n2
Generation 2
X
Evolution of Artificial Neural NetworksCircles=neurons; arrows=synaptic connections
fitness: 2.9 meters
fitness: 2.6 meters
m1m2 mp
i1 i2 in
s1 s2 sm
m1m2 mp
i1 i2 in
s1 s2 sm
network 1
network n
fitness: 2.3 meters
fitness: 2.8 meters
Generation 1
m1m2 mp
i1 i2 in
s1 s2 sm
m1m2 mp
i1 i2 in
s1 s2 sm
network n1
network n2
Generation 2
X
Evolution of Artificial Neural NetworksCircles=neurons; arrows=synaptic connections
Generation 3
m1m2 mp
i1 i2 in
s1 s2 sm
m1m2 mp
i1 i2 in
s1 s2 sm
network 1
network n
fitness: 2.3 meters
fitness: 2.8 meters
Generation 1
m1m2 mp
i1 i2 in
s1 s2 sm
m1m2 mp
i1 i2 in
s1 s2 sm
network n1
network n2
Generation 2
X
fitness: 2.9 meters
fitness: 2.6 meters
m1m2 mp
i1 i2 in
s1 s2 sm
m1m2 mp
i1 i2 in
s1 s2 sm
network n1,1
network n1,2
fitness: 3.1 meters
fitness: 1.4 meters
Floreano & Mondada, 1994Automatic creation of an autonomous agent: Genetic evolution of a neural-networkdriven robot
Floreano & Mondada, 1994Automatic creation of an autonomous agent: Genetic evolution of a neural-networkdriven robot
Husbands, Harvey & Cliff, 1994Seeing The Light: Articial Evolution, Real Vision
Husbands, Harvey & Cliff, 1994Seeing The Light: Articial Evolution, Real Vision
What’s Modeled and What Isn’t
I Modeled:
I Heritable genetic variation → differences in reproduction rateI Physical impact of the robot on the environmentI Physical impact of the environment on the robotI Point mutationI Evolved changes in synaptic strength
I Not Modeled:
I Sexual recombinationI DiploidyI Evolution of the architecture of the nervous systemI Evolution of the body planI Evolution of developmentI EpigeneticsI Sexual selectionI Neutral mutationI ...
Evolving the Nervous System and Body Plan
I Modeled:
I Heritable genetic variation → differences in reproduction rateI Physical impact of the robot on the environmentI Physical impact of the environment on the robotI Point mutationI Evolved changes in synaptic strengthI Evolution of the body plan
I Not Modeled:
I Sexual recombinationI DiploidyI Evolution of the architecture of the nervous systemI Evolution of developmentI EpigeneticsI Sexual selectionI Neutral mutationI ...
Karl Sims, 1992
The GOLEM ProjectLipson & Pollack, Science, 2000
d = 59.6cm d = 85.1cm d = 38.5cm
a c e
b d fd = 22.5cm d = 23.4cm d = 38.4cm
The GOLEM ProjectLipson & Pollack, Science, 2000
a b
c d
Tensegrity Robots: Rieffel, Valero-Cuevas & Lipson, 2009[Video courtesy of NASA; 2014]
Evolving Active Categorical PerceptionBongard, 2011, IEEE Trans Evol Comp
Cornell’s Simulated Soft RobotsCheney, MacCurdy, Clune & Lipson. (2013). In Procs. of the Genetic and Evolutionary Computation Conf.
HyperNEAT for Soft RobotsCheney, MacCurdy, Clune & Lipson. (2013). In Procs. of the Genetic and Evolutionary Computation Conf.
Morphological and Environmental ComplexityAuerbach & Bongard, 2014, PLoS Comp Bio.
What’s Modeled and What Isn’t
I Modeled:
I Heritable genetic variation → differences in reproduction rateI Physical impact of the robot on the environmentI Physical impact of the environment on the robotI Point mutationI Evolved changes in synaptic strength
I Not Modeled:
I Sexual recombinationI DiploidyI Evolution of the architecture of the nervous systemI Evolution of the body planI Evolution of developmentI EpigeneticsI Sexual selectionI Neutral mutationI ...
“Robo Evo Devo”
I Modeled:
I Heritable genetic variation → differences in reproduction rateI Physical impact of the robot on the environmentI Physical impact of the environment on the robotI Point mutationI Evolved changes in synaptic strengthI Evolution of Development
I Not Modeled:
I Sexual recombinationI DiploidyI Evolution of the architecture of the nervous systemI Evolution of the body planI EpigeneticsI Sexual selectionI Neutral mutationI ...
Eggenberger, 1997Evo-devo through differential gene expression. Procs of ECAL
Bongard & Pfeifer, 2001Procs of GECCO
Bongard & Pfeifer, 2001Procs of GECCO
Doursat, Sayama & Michel (2012)Morphogenetic Engineering. Springer. “Self-architecturing” systems
Robo-Evo-Devo produces more robust controllers faster.Bongard, 2011, PNAS
Robo-Evo:
Robo-Evo-Devo:
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