Evolving Virtual Life Language, digital DNA, hyperspace for - - PDF document

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Evolving Virtual Life

Kenneth Holmlund, holmlund@hpc2n.umu.se VRlab/HPC2N, Umeå University

Foundation

• Evolutionary algorithms
• Language, digital DNA, hyperspace for optimization
• Physics based simulation
• Rigid body dynamics with contacts, joints, constraints and friction
• Sensors and effectors
• Control mechanism
• Visualization and computer graphics (and physical implementation)
• Real-time and/or off-line rendering
• Requires quite a machinery!

Why, what, where?

Scientific (what is life, evolution, GA, etc.?) Engineering (evolutionary and implicit design) Art and entertainment (beautiful images, animations,

interactivity)

Cult (watch out!) Expectations are very high – but not that incredibly

much has happened since 1994 when the area was born! As usual, short term expectations unrealistic, while long term effect and under estimated.

Karl Sims “Evolving Virtual Creatures”

SIGGRAPH 1994, Alife IV Proceedings 1994 Was working for Thinking Machines at the time. Several previous publications in genetic art. Inspired by e.g. Koza (who proposed an L-system like

methodology, with repeating structures)

Sims’ SIGGRAPH 1994 Video Sim’s method and results

Two main papers. First on basic method and

different selections (previous video). Second on co- evolution, i.e. competing creatures.

"Evolving Virtual Creatures" , K.Sims, Computer

Graphics (Siggraph '94 Proceedings), July 1994, pp.15-22

• "Evolving 3D Morphology and Behavior by

Competition“, K.Sims, Artificial Life IV Proceedings, ed.by Brooks & Maes, MIT Press, 1994, pp.28-39.

2 System representation

Genotype Phenotype (directed graph) (hierarchy of 3d parts)

Directed graph for representation

Starting at root node Nodes

Information Dimensions Joint-type Joint-limits Recursive-limit Neurons Connections Child Node Position Orientation Scale Reflection

Control

Brain is also a directed graph of neurons that can do sum, product, divide, sum-threshold, greater than, sogn-of, abs, max, min, cos, sin, oscillate, etc for input/output processing Applied as forces and torques Joint angle Contacts (self/environment) Photo sensors

Combining morphology and control Combining morphology and control

Nested graph Blocks of neural circuitry are replicated with

each instanced part (otherwise phase space wille be too big and unconstrained)

Physical simulation

Rigid-body simulation

Collision detection (bounding box hierarchies) Collision response (projection at high v + penalty at low v) Contacts Friction and viscosity Forces Torques Mass and inertia Featherstone’s algorithm

Creatures exploit all bugs! This includes violated

conservation of energy and momentum, as well as numerical errors! (self slapping, rotating paddle, falling over on box, etc.)

3 Selection – genetic pressure

Behaviour

Swimming ”Walking” Jumping Follow

Fitness function computed at each step. Interactive selection based on e.g. aesthetics

Evolving the system

Start configuration

Minimalistic, random Pre-evolved creatures (also based on completely

different fitness functions)

User designed creatures

Compute survival ratio Compute fitness value and select the fittest Reproduce Evolve and recompute fitness value etc.

Evolving the graph (”DNA”)

Directed graph mutation

Internal node parameters Add random node Connection parameters altered randomly (small) Add/remove connections randomly Remove unconnected elements Mutation frequency for each parameter type

Scale mutation frequency with inverse graph

size (otherwise evolution easily becomes spurious)

Mating graphs

Method choosen randomly for each child. 40% asexual 30% crossover 30% grafting

Crossover point for copying From parents to child. A node of a parent connected to a node of the other parent.

Running the simulation

Connection Machine CM-5 with 32

processors – 3 Hours

Population of 300 Survival ratio 1/5 100 Generations 1-5 time steps per frame of 1/30 s

Results

Homogeneity Swimmers

Paddlers Tail-waggers

Walkers

Lizard-like Pushers/Pullers Hoppers

Followers

Steering Fins Paddlers

4 Co-evolution

Second paper (Alife IV) Two creatures compete about possesion about a

block

Co-evolution Co-evolution Co-evolution Co-evolution Follow up by Tom Ray

Zoology professor Lots’a spare time in the jungle… Developed Tierra (http://www.his.atr.jp/~ray/tierra/) Did Alife 1990-2001 (digital evolution) Virtual Aesthetic Creatures project

Variations in selection pressure (aesthetic, emotional,

• empathetic. Love, …etc)

Prettier rendering and commercial movie Based on Mathengine 1.x physics toolkit (co-developed by

Claude Lacoursiere that works with us).

See http://www.his.atr.jp/~ray/ Software: VirtualLife (still works, but needs Mathengine

license file. Ask me if you need help fixing it..).

5 Ray’s Creatures Conclusions

• How far can we take this?
• Not entirely understood
• Robotics researchers have created simulations that are based on real self-repeating and varying

building blocks, such that the final result actually can be manufactured. Very interesting, but not really conclusive.

• Marriages between computing science, physics and biology are fruitful!
• It seems that not many are able to integrate evolutionary algorithms, robust physics based

simulation and computer graphics – and at the same time also ask the relevant scientific questions.

• For some recent research in the area see the work of e.g. Chris Adami:

http://www.krl.caltech.edu/~adami/ and Richard Lenski: http://www.msu.edu/user/lenski/ They have published lots of ground breaking results, but as far as I know nothing where they also do physics simulation.

• Also see this book: Evolutionary Robotics - The Biology, Intelligence, and Technology of Self-

Organizing Machines Stefano Nolfi and Dario Floreano http://mitpress.mit.edu/catalog/item/default.asp?ttype=2&tid=3684

• Some recent examples following up Sims’ work: http://163.152.22.77/shim/research.htm
• Tim Taylor and Colm Massey at Mathengine also did some follow up on Sims’ work:

http://homepages.inf.ed.ac.uk/timt/demos/mathengine/index.html