Sandpile Model and XY Model (Tim)
Sandpile Model and XY Model (Tim)
Height models
•
Height models
Random initialization sandpile model
•
Random initialization sandpile model
Continuous model
•
Continuous model
Gaussian topples
•
Gaussian topples
Local rule with monodromies
•
Local rule with monodromies
Stable structures with topological monodromies
•
Stable structures with topological monodromies
More stabke structures
•
More stabke structures
Optical filtering, Van der Pol osc., Kuramoto?
•
Optical filtering, Van der Pol osc., Kuramoto?
Modern Implementation of Tierra (Ariane)
Modern Implementation of Tierra (Ariane)
Tierra, creatures=programs, 32 instr., self-rep
•
Tierra, creatures=programs, 32 instr., self-rep
Aim: study evolution
•
Aim: study evolution
Tierra: memory, creature, slicer, reeaper
•
Tierra: memory, creature, slicer, reeaper
Creature's CPU: 4 registers, 1 stack
•
Creature's CPU: 4 registers, 1 stack
Instructions: some no-op patterns (to allow programs to find each other), some copy stuff, some memory allocation, some divide
•
Instructions: some no-op patterns (to allow programs to find each other), some copy stuff, some memory allocation, some divide
Ancestor code: the original self-replicator
•
Ancestor code: the original self-replicator
We can look for the address of the beginning and the address of the end
•
We can look for the address of the beginning and the address of the end
The ancestors replicate, and they are suddenly replaced by a new species after a while
•
The ancestors replicate, and they are suddenly replaced by a new species after a while
Problem of roaming CPUs
•
Problem of roaming CPUs
Topological-Informed CAs (Flavia)
Topological-Informed CAs (Flavia)
Some algebraic topology ideas: simplicial complex
•
Some algebraic topology ideas: simplicial complex
Meshes as simplicial complexes, multi-order neighbors... work with triangular mesh
•
Meshes as simplicial complexes, multi-order neighbors... work with triangular mesh
TopoCA: a totalistic CA
•
TopoCA: a totalistic CA
Binary state variables (torch tensors)
•
Binary state variables (torch tensors)
Adjacency matrices across levels
•
Adjacency matrices across levels
Rule: conditions for activities, sequential update: Nodes[2]->Edges[1,2]->Triangles[1,2]
•
Rule: conditions for activities, sequential update: Nodes[2]->Edges[1,2]->Triangles[1,2]
Optimization of computations
•
Optimization of computations
Node update using roll
•
Node update using roll
Higher-order updates, triangle-to-edge, ...
•
Higher-order updates, triangle-to-edge, ...
Drawing: classic, intensity 1C, intensity 3C
•
Drawing: classic, intensity 1C, intensity 3C
Some TopoCA stable patterns appear typically
•
Some TopoCA stable patterns appear typically
Some cool gliders appear, some regeneration
•
Some cool gliders appear, some regeneration
Can we use topological invariants?
•
Can we use topological invariants?
Phylogenetic Trees in Simulated Evolution (Raphael)
Phylogenetic Trees in Simulated Evolution (Raphael)
Pylogenetic trees
•
Pylogenetic trees
Creating phylogenetic trees: need evolution, reproduction, ...
•
Creating phylogenetic trees: need evolution, reproduction, ...
World Generation using Perlin Noise
•
World Generation using Perlin Noise
Binary World Map from World
•
Binary World Map from World
Asexually Reproducing Organisms
•
Asexually Reproducing Organisms
Growing population, organisms do not age
•
Growing population, organisms do not age
Migration w/ Fick's diffusion law discretized
•
Migration w/ Fick's diffusion law discretized
Migrating Organisms: when a region transitions from ocean to land, all organisms die
•
Migrating Organisms: when a region transitions from ocean to land, all organisms die
Simulating Genomes, 64-bit genome
•
Simulating Genomes, 64-bit genome
Asexually Reproducing Species
•
Asexually Reproducing Species
Simulate Mutation&Speciation, Hamming Threshold
•
Simulate Mutation&Speciation, Hamming Threshold
Phyl. tree: a bit disappointing, need selection
•
Phyl. tree: a bit disappointing, need selection
Simulating Natural Selection; simplified model
•
Simulating Natural Selection; simplified model
Target Genomo / Ocean Coverage / fraction
•
Target Genomo / Ocean Coverage / fraction
Natural Selection: Hamming distance
•
Natural Selection: Hamming distance
Tree / Prune Branches / Extant lineages
•
Tree / Prune Branches / Extant lineages
Extinction Event: Pulse/Aftermath/Revitalize
•
Extinction Event: Pulse/Aftermath/Revitalize
Particle Life with Cells (Alexandre)
Particle Life with Cells (Alexandre)
Cell Type CA, Physics-Inspired Interaction
•
Cell Type CA, Physics-Inspired Interaction
Attraction-Repulsion Based on Springs
•
Attraction-Repulsion Based on Springs
Cell-Type CA
•
Cell-Type CA
Particle Life: Physical World: simple scheme between two things attractive vs repulsive forces
•
Particle Life: Physical World: simple scheme between two things attractive vs repulsive forces
Some update of position rules
•
Some update of position rules
Cell-Type Interactions
•
Cell-Type Interactions
Delay before 'death' or 'convertibility'
•
Delay before 'death' or 'convertibility'
Some simulation rules within PyCA
•
Some simulation rules within PyCA
Particle Life with CA
•
Particle Life with CA
Some simulation samples within PyCA
•
Some simulation samples within PyCA
Mace Lenia (Michael)
Mace Lenia (Michael)
Lenia, with a kernel, growth function
•
Lenia, with a kernel, growth function
MaCELenia: Mass Conservation Rule
•
MaCELenia: Mass Conservation Rule
How to transfer parameters
•
How to transfer parameters
MaceLeniaXParam, varying parameters through space
•
MaceLeniaXParam, varying parameters through space
Adding several species
•
Adding several species
Cross the parameters between Lenia species
•
Cross the parameters between Lenia species
Questions: random weight changes, spontaneous gene modification
•
Questions: random weight changes, spontaneous gene modification
Simple CAs (Lucas)
Simple CAs (Lucas)
3-Channel CA, 2 states
•
3-Channel CA, 2 states
Many possible rules
•
Many possible rules
Update Rule Format
•
Update Rule Format
Restrict to totalistic rules for each channel
•
Restrict to totalistic rules for each channel
Example: can check if sum of neighbors is >3 in 0, and can increase the a counter
•
Example: can check if sum of neighbors is >3 in 0, and can increase the a counter
Each update rule can be summarized by if statements, each if statement has 6 parameters
•
Each update rule can be summarized by if statements, each if statement has 6 parameters
Random rules
•
Random rules
Evolutionary algorithm to explore, evaluate with a fitness metric, mutate the survivors
•
Evolutionary algorithm to explore, evaluate with a fitness metric, mutate the survivors
Fitness: entropy + temporal smoothness
•
Fitness: entropy + temporal smoothness
Temporal evolution of fitness metric
•
Temporal evolution of fitness metric
Fitness: temporal evolution + entropy
•
Fitness: temporal evolution + entropy
How to see gliders? We can see gliders
•
How to see gliders? We can see gliders
.