biosim4.ini

# biosim4.ini
# biosim4.ini is the default config file for the simulator.
# The config filename is determined in simulator() in simulator.cpp.
# The config file is parsed by class ParamManager, see params.cpp and params.h.
# Although not foolproof, the config file can be modified during a simulation
# run and the param manager will make any new params available to the simulator
# after the end of the current simulator step or after the end of the current
# generation.

# numThreads must be 1 or greater. Best value is less than or equal to
# the number of CPU cores.
numThreads = 4

# sizeX, sizeY define the size of the 2D world. Minimum size is 16,16.
# Maximum size is 32767, 32767.
sizeX = 128
sizeY = 128

# Population at the start of each generation. Maximum value = 32766.
population = 3000

# Number of simulation steps per generation. Range 1..INT_MAX.
stepsPerGeneration = 300

# The simulator will stop when the generation number == maxGenerations.
# Range 1..INT_MAX
maxGenerations = 200000

# genomeInitialLengthMin and genomeInitialLengthMax should be set to
# the same value. (For future use, the max length might be larger to
# allow mutations that lengthen the genome.) Range 1..INT_MAX and
# must be no larger than genomeMaxLength. The range of genomeMaxLength
# is genomeInitialLengthMax..INT_MAX.
genomeInitialLengthMin = 24
genomeInitialLengthMax = 24
genomeMaxLength = 300

# maxNumberNeurons is the maximum number of internal neurons that may
# be addressed by genes in the genome. Range 1..INT_MAX.
maxNumberNeurons = 5

# If killEnable is true and the "kill" action neuron is enabled in
# sensors-actions.h and compiled in, then agents are permitted to
# kill their neighbor in the adjacent location in the direction of
# forward movement. If false, the neighbors are safe.
killEnable = false

# If sexualReproduction is false, newborns inherit the genes from a
# single parent. If true, newborns inherit a mixture of genes from
# two parents.
sexualReproduction = true

# If chooseParentByFitness is false, then every agent that survives the
# selection criterion has equal chance of reproducing. If true, then
# preference is given to those parents who passed the selection criterion
# with a greater score. Fitness scores are determined in survival-criteria.cpp.
chooseParentsByFitness = true

# pointMutationRate is the probability per gene of having a single-bit
# mutation during spawning. Range 0.0 .. 1.0. A reasonable range is
# 0.0001 to 0.01.
pointMutationRate = 0.001

# geneInsertionDeletionRate and deletionRatio are for future use to
# allow mutations that lengthen or shorten the genome. Ignored for now.
geneInsertionDeletionRate = 0.0
deletionRatio = 0.5

# responsivenessCurveKFactor is a small positive integer that determines
# the shape of the curve that determines how reactive an agent is to its
# sensory inputs. Typical values are # 1, 2, 3, or 4, but greater values
# are allowed experimentally.
responsivenessCurveKFactor = 2

# populationSensorRadius is the radius in which the population sensor
# looks for neighbors. Floating point value. A value of 1.5 includes
# all the immediate eight-neighborhood. Larger values incur exponentially
# increasing processor overhead. Range 0.5 up to (float)max(sizeX, sizeY).
populationSensorRadius = 2.5

# longProbeDistance is the default distance that the long-probe sensors
# are able to see. Applies to long-probe population sensor and long-probe
# signal (pheromone) sensor. Range 1..INT_MAX.
longProbeDistance = 16

# shortProbeBarrierDistance is the distance that the short-probe sensor
# can see. Range 1..INT_MAX.
shortProbeBarrierDistance = 4

# signalSensorRadius is the radius in which the signal (pheromone) sensor
# looks for pheromones. Floating point value. A value of 1.5 includes
# all the immediate eight-neighborhood. Larger values incur exponentially
# increasing processor overhead. Range 0.5 up to (float)max(sizeX, sizeY).
signalSensorRadius = 2.0

# signalLayers defines the number of pheromone layers. Must be 1 for now.
# Values > 1 are for future use.
signalLayers = 1

# imageDir is the relative or absolute directory path where generation
# movies are created.
imageDir = images

# logDir is the relative or absolute directory path where text log files
# are created.
logDir = logs

# displayScale scales the generation movie. Typical values are
# 1 for actual size, or 2, 4, 8, 16, or 32 to scale up the movie.
displayScale = 8

# agentSize controls the size of the dot used to represent an agent
# in the generation movie. Typical value is displayScale / 2.
agentSize = 4

# If videoSaveFirstFrames is 0, then only the parameter videoStride controls
# how often generation movies are made. If videoSaveFirstFrames is nonzero,
# then generation movies will also be generated for every generation from 0
# through videoSaveFirstFrames (because the first few generations are often
# the most interesting). Range 1..INT_MAX.
videoSaveFirstFrames = 2

# updateGraphLog can be set to true to cause the simulator program to
# invoke graphlog.gp to update the simulation progress graph. If true,
# then updateGraphLogStride controls how often it is invoked. If
# updateGraphLog is false, then the simulator program will not invoke
# graphlog.gp.
updateGraphLog = true

# If saveVideo is true, the simulator program will create generation
# movies in the directory named by imageDir at the intervals set by
# videoSaveFirstFrames and videoStride.
saveVideo = true

# videoStride determines how often generation movies will be created.
# Also see saveVideo and videoSaveFirstFrames. Range 1..INT_MAX.
videoStride = 25

# updateGraphLogStride determines how often the simulation progress graph
# is updated by direct invocation of graphlog.gp. Ignored if updateGraphLog
# is false. updateGraphLogStride may be a positive integer from 1 to INT_MAX,
# or may be set to the string videoStride to use the value of videoStride.
updateGraphLogStride = videoStride

# genomeAnalysisStride determines how often the simulator will print genomic
# statistics. The stats are printed to stdout when the generation number
# modulo genomeAnalysisStride == 0. The value may be a positive integer from
# 1 to INT_MAX, or may be set to the string videoStride to use the value of
# videoStride.
genomeAnalysisStride = videoStride

# When the genomic statistics are printed (see genomeAnalysisStride), the
# method used to measure genome diversity in the population is determined
# by genomeComparisonMethod. May be set to 0 for Jaro-Winkler method (useful
# for future use if genomes are allowed to grow or shrink in size); or 1
# for a Hamming measure bit-by-bit, or 2 for a Hamming measure byte-by-byte.
# Typically set to 1.
genomeComparisonMethod = 1

# When genomic statistics are printed (see genomeAnalysisStride), the number
# of genomes sampled from the population and printed to stdout is determined
# by displaySampleGenomes. Range 0 to population size.
displaySampleGenomes = 5

# challenge determines the selection criterion for reproduction. This is
# typically always under active development. See survival-criteria.cpp for
# more information.
# 0 = circle
# 1 = right half
# 2 = right quarter
# 3 = neighbor count
# 4 = center weighted
# 40 = center unweighted
# 5 = corner 1/4 radius
# 6 = corner 1/4 radius weighted
# 7 = migrate distance
# 8 = center sparse
# 9 = left eighth
# 10 = radioactive walls
# 11 = against any wall
# 12 = touch any wall any time
# 13 = east-west eighths
# 14 = near barrier
# 15 = pairs
# 16 = contact location sequence
# 17 = altruism, circle + NE corner
challenge = 6

# The simulator supports a feature called "barriers." Barriers are locations
# in the simulated 2D world where agents may not occupy. The value of
# barrierType is typically under active development. See createBarrier.cpp
# for more information. Also see replaceBarrierType.
# 0 = none
# 1 = vertical bar constant location
# 2 = vertical bar random locations
# 3 = five staggered vertical bars
# 4 = horiz bar constant location north center
# 5 = floating islands
# 6 = sequence of spots
barrierType = 0

# The barrier type will automatically change from barrierType to
# replaceBarrierType at the generation specified by
# replaceBarrierTypeGenerationNumber. Range 0..INT_MAX, or set to -1 to
# disable.
replaceBarrierType = 0
replaceBarrierTypeGenerationNumber = -1

# If true, then the random number generator (RNG) will be seeded by the value
# in RNGSeed, causing each thread to receive a deterministic sequence from
# the RNG. If false, the RNG will be randomly seeded and program output will
# be non-deterministic.
deterministic = false

# If deterministic is true, the random number generator will be seeded with
# this value. If deterministic is false, this value is ignored. Legal values
# are integers 0 to 4294967295.
RNGSeed = 12345678