evolutionary robotics tutorial

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: