GenMan class, available in: Global contextManages various genetic operations, using appropriate operators for the argument genotype format.This class has 207 members:
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int gen_hist0 .. 1 (false/true)
default=0		Remember history of genetic operationsRequired for phylogenetic analysis
int gen_hilite0 .. 1 (false/true)
default=1		Use syntax highlightingUse colors for genes?
(slows down viewing/editing of huge genotypes)
int gen_extmutinfo0 .. 2
  • 0 = Off (default)
  • 1 = Method ID
  • 2 = Method description
    		• Extended mutation infoIf active, information about employed mutation method will be stored in the 'info' field of each mutated genotype.
    srotarepo evitcA :sciteneG
    int _property_changed_index ROLast changed property index
    string _property_changed_id ROLast changed property id
    int genoper_f0 RO0 .. 0
  • 0 = Default
    		• Operators for f0
    int genoper_f0s RO0 .. 0
  • 0 = Default
    		• Operators for f0s
    int genoper_f1 RO0 .. 0
  • 0 = Default
    		• Operators for f1
    int genoper_f4 RO0 .. 0
  • 0 = Default
    		• Operators for f4
    int genoper_f8 RO0 .. 0
  • 0 = Default
    		• Operators for f8
    int genoper_f9 RO0 .. 0
  • 0 = Default
    		• Operators for f9
    int genoper_fF RO0 .. 0
  • 0 = Default
    		• Operators for fF
    int genoper_fn RO0 .. 0
  • 0 = Default
    		• Operators for fn
    int genoper_fB RO0 .. 0
  • 0 = Default
    		• Operators for fB
    int genoper_fH RO0 .. 0
  • 0 = Default
    		• Operators for fH
    int genoper_fL RO0 .. 0
  • 0 = Default
    		• Operators for fL
    int genoper_fS RO0 .. 0
  • 0 = Default
    		• Operators for fS
    dda ot snorueN :sciteneG
    int neuadd_N0 .. 1 (false/true)Neuron (N)Standard neuron

    Characteristics:
    supports any number of inputs
    provides output value
    does not require location in body


    Properties:
    Inertia (in) float 0..1 (default 0.8)
    Force (fo) float 0..999 (default 0.04)
    Sigmoid (si) float -99999..99999 (default 2)
    State (s) float -1..1 (default 0)
    int neuadd_Nu0 .. 1 (false/true)Unipolar neuron [EXPERIMENTAL!] (Nu)Works like standard neuron (N) but the output value is scaled to 0...+1 instead of -1...+1.
    Having 0 as one of the saturation states should help in "gate circuits", where input signal is passed through or blocked depending on the other singal.

    Characteristics:
    supports any number of inputs
    provides output value
    does not require location in body


    Properties:
    Inertia (in) float 0..1 (default 0.8)
    Force (fo) float 0..999 (default 0.04)
    Sigmoid (si) float -99999..99999 (default 2)
    State (s) float -1..1 (default 0)
    int neuadd_G0 .. 1 (false/true)Gyroscope (G)Tilt sensor.
    Signal is proportional to sin(angle) = most sensitive in horizontal orientation.
    0=the stick is horizontal
    +1/-1=the stick is vertical

    Characteristics:
    does not use inputs
    provides output value
    should be located on a Joint
    int neuadd_Gpart0 .. 1 (false/true)Part Gyroscope (Gpart)Tilt sensor. Signal is directly proportional to the tilt angle.
    0=the part X axis is horizontal
    +1/-1=the axis is vertical

    Characteristics:
    does not use inputs
    provides output value
    should be located on a Part


    Properties:
    rotation.y (ry) float -6.282..6.282 (default 0)
    rotation.z (rz) float -6.282..6.282 (default 0)
    int neuadd_T0 .. 1 (false/true)Touch (T)Touch and proximity sensor (Tcontact and Tproximity combined)
    -1=no contact
    0=just touching
    >0=pressing, value depends on the force applied (not implemented in ODE mode)

    Characteristics:
    does not use inputs
    provides output value
    should be located on a Part


    Properties:
    Range (r) float 0..1 (default 1)
    rotation.y (ry) float -6.282..6.282 (default 0)
    rotation.z (rz) float -6.282..6.282 (default 0)
    int neuadd_Tcontact0 .. 1 (false/true)Touch contact (Tcontact)Touch sensor.
    -1=no contact
    0=the Part is touching the obstacle
    >0=pressing, value depends on the force applied (not implemented in ODE mode)

    Characteristics:
    does not use inputs
    provides output value
    should be located on a Part
    int neuadd_Tproximity0 .. 1 (false/true)Touch proximity (Tproximity)Proximity sensor detecting obstacles along the X axis.
    -1=distance is "r" or more
    0=zero distance

    Characteristics:
    does not use inputs
    provides output value
    should be located on a Part


    Properties:
    Range (r) float 0..1 (default 1)
    rotation.y (ry) float -6.282..6.282 (default 0)
    rotation.z (rz) float -6.282..6.282 (default 0)
    int neuadd_S0 .. 1 (false/true)Smell (S)Smell sensor. Aggregated "smell of energy" experienced from all energy objects (creatures and food pieces).
    Close objects have bigger influence than the distant ones: for each energy source, its partial feeling is proportional to its energy/(distance^2)

    Characteristics:
    does not use inputs
    provides output value
    should be located on a Part
    int neuadd_Constant0 .. 1 (false/true)Constant (*)Constant value

    Characteristics:
    does not use inputs
    provides output value
    does not require location in body
    int neuadd_Bend_muscle0 .. 1 (false/true)Bend muscle (|)Characteristics:
    uses single input
    does not provide output value
    should be located on a Joint


    Properties:
    power (p) float 0..1 (default 0.25)
    bending range (r) float 0..1 (default 1)
    int neuadd_Rotation_muscle0 .. 1 (false/true)Rotation muscle (@)Characteristics:
    uses single input
    does not provide output value
    should be located on a Joint


    Properties:
    power (p) float 0..1 (default 1)
    int neuadd_M0 .. 1 (false/true)Muscle for solids (M)Characteristics:
    uses single input
    does not provide output value
    should be located on a Joint


    Properties:
    power (p) float 0..1 (default 1)
    axis (a) integer 0..1 (default 0)
    int neuadd_D0 .. 1 (false/true)Differentiate (D)Calculate the difference between the current and previous input value. Multiple inputs are aggregated with respect to their weights

    Characteristics:
    supports any number of inputs
    provides output value
    does not require location in body
    int neuadd_Fuzzy0 .. 1 (false/true)Fuzzy system [EXPERIMENTAL!] (Fuzzy)Refer to publications to learn more about this neuron.

    Characteristics:
    supports any number of inputs
    provides output value
    does not require location in body


    Properties:
    number of fuzzy sets (ns) integer
    number of rules (nr) integer
    fuzzy sets (fs) string (default "")
    fuzzy rules (fr) string (default "")
    int neuadd_VEye0 .. 1 (false/true)Vector Eye [EXPERIMENTAL!] (VEye)Refer to publications to learn more about this neuron.

    Characteristics:
    uses single input
    provides output value
    should be located on a Part


    Properties:
    target.x (tx) float
    target.y (ty) float
    target.z (tz) float
    target shape (ts) string (default "")
    perspective (p) float 0.1..10 (default 1)
    scale (s) float 0.1..100 (default 1)
    show hidden lines (h) integer 0..1 (default 0)
    output lines count (each line needs four channels) (o) integer 0..99 (default 0)
    debug (d) integer 0..1 (default 0)
    int neuadd_VMotor0 .. 1 (false/true)Visual-Motor Cortex [EXPERIMENTAL!] (VMotor)Must be connected to the VEye and properly set up. Refer to publications to learn more about this neuron.

    Characteristics:
    supports any number of inputs
    provides output value
    does not require location in body


    Properties:
    number of basic features (noIF) integer
    number of degrees of freedom (noDim) integer
    parameters (params) string
    int neuadd_Sti0 .. 1 (false/true)Sticky [EXPERIMENTAL!] (Sti)Characteristics:
    uses single input
    does not provide output value
    should be located on a Part
    int neuadd_LMu0 .. 1 (false/true)Linear muscle [EXPERIMENTAL!] (LMu)Characteristics:
    uses single input
    does not provide output value
    should be located on a Joint


    Properties:
    power (p) float 0.01..1 (default 1)
    int neuadd_Water0 .. 1 (false/true)Water detector (Water)Output signal:
    0=on or above water surface
    1=under water (deeper than 1)
    0..1=in the transient area just below water surface

    Characteristics:
    does not use inputs
    provides output value
    should be located on a Part
    int neuadd_Energy0 .. 1 (false/true)Energy level (Energy)The current energy level divided by the initial energy level.
    Usually falls from initial 1.0 down to 0.0 and then the creature dies. It can rise above 1.0 if enough food is ingested

    Characteristics:
    does not use inputs
    provides output value
    does not require location in body
    int neuadd_Ch0 .. 1 (false/true)Channelize (Ch)Combines all input signals into a single multichannel output; Note: ChSel and ChMux are the only neurons which support multiple channels. Other neurons discard everything except the first channel.

    Characteristics:
    supports any number of inputs
    provides output value
    does not require location in body
    int neuadd_ChMux0 .. 1 (false/true)Channel multiplexer (ChMux)Outputs the selected channel from the second (multichannel) input. The first input is used as the selector value (-1=select first channel, .., 1=last channel)

    Characteristics:
    uses 2 inputs
    provides output value
    does not require location in body
    int neuadd_ChSel0 .. 1 (false/true)Channel selector (ChSel)Outputs a single channel (selected by the "ch" parameter) from multichannel input

    Characteristics:
    uses single input
    provides output value
    does not require location in body


    Properties:
    channel (ch) integer
    int neuadd_Rnd0 .. 1 (false/true)Random noise (Rnd)Generates random noise (subsequent random values in the range of -1..+1)

    Characteristics:
    does not use inputs
    provides output value
    does not require location in body
    int neuadd_Sin0 .. 1 (false/true)Sinus generator (Sin)Output frequency = f0+input

    Characteristics:
    uses single input
    provides output value
    does not require location in body


    Properties:
    base frequency (f0) float -1..1 (default 0.0628319)
    time (t) float 0..6.28319 (default 0)
    0f :sciteneG
    int f0_nodel_tag0 .. 1 (false/true)
    default=1    		Respect the 'delete inhibit' tagYou can tag elements using their 'i' field and the i="mi=d" tag.
    Mutations will not delete such elements.
    The i="mi=dm" combination is allowed.
    int f0_nomod_tag0 .. 1 (false/true)
    default=1    		Respect the 'modify inhibit' tagYou can tag elements using their 'i' field and the i="mi=m" tag.
    Mutations will not modify properties of such elements.
    The i="mi=md" combination is allowed.
    straP :0f :sciteneG
    float f0_p_new0 .. 100
    default=4.0    		New part
    float f0_p_del0 .. 100
    default=4.0    		Delete part
    float f0_p_swp0 .. 100
    default=1.0    		Swap parts
    float f0_p_pos0 .. 100
    default=4.0    		Position
    float f0_p_den0 .. 100
    default=0.0    		DensityDensity only has an influence under water
    float f0_p_frc0 .. 100
    default=1.0    		Friction
    float f0_p_ing0 .. 100
    default=0.0    		Ingestion
    float f0_p_asm0 .. 100
    default=0.0    		AssimilationThe interpretation and influence of this property must be implemented by the experiment definition
    stnioJ :0f :sciteneG
    float f0_j_new0 .. 100
    default=4.0    		New joint
    float f0_j_del0 .. 100
    default=1.0    		Delete joint
    float f0_j_stm0 .. 100
    default=0.0    		StaminaThe interpretation and influence of this property must be implemented by the experiment definition
    float f0_j_stf0 .. 100
    default=0.0    		Stiffness
    float f0_j_rsf0 .. 100
    default=0.0    		Rotational stiffness
    float f0_j_vred0 .. 100
    default=0.0    		Visual: red
    float f0_j_vgrn0 .. 100
    default=0.0    		Visual: green
    float f0_j_vblu0 .. 100
    default=0.0    		Visual: blue
    snorueN :0f :sciteneG
    float f0_n_new0 .. 100
    default=3.0    		New neuron
    float f0_n_del0 .. 100
    default=3.0    		Delete neuron
    float f0_n_prp0 .. 100
    default=1.0    		Change properties
    snoitcennoC :0f :sciteneG
    float f0_c_new0 .. 100
    default=2.0    		New connection
    float f0_c_del0 .. 100
    default=2.0    		Delete connection
    float f0_c_wei0 .. 100
    default=1.0    		Change weight
    s0f :sciteneG
    int f0s_nodel_tag0 .. 1 (false/true)
    default=1    		Respect the 'delete inhibit' tagYou can tag elements using their 'i' field and the i="mi=d" tag.
    Mutations will not delete such elements.
    The i="mi=dm" combination is allowed.
    int f0s_nomod_tag0 .. 1 (false/true)
    default=1    		Respect the 'modify inhibit' tagYou can tag elements using their 'i' field and the i="mi=m" tag.
    Mutations will not modify properties of such elements.
    The i="mi=md" combination is allowed.
    straP :s0f :sciteneG
    int f0s_circle_section0 .. 1 (false/true)
    default=1    		Ensure circle sectionEnsure that ellipsoids and cylinders have circle cross-section
    int f0s_use_elli0 .. 1 (false/true)
    default=1    		Use ellipsoids in mutationsUse ellipsoids in mutations
    int f0s_use_cub0 .. 1 (false/true)
    default=1    		Use cuboids in mutationsUse cuboids in mutations
    int f0s_use_cyl0 .. 1 (false/true)
    default=1    		Use cylinders in mutationsUse cylinders in mutations
    float f0s_p_new0 .. 100
    default=5.0    		New part
    float f0s_p_del0 .. 100
    default=5.0    		Delete part
    float f0s_p_swp0 .. 100
    default=10.0    		Swap parts
    float f0s_p_pos0 .. 100
    default=10.0    		Position
    float f0s_p_rot0 .. 100
    default=10.0    		Rotation
    float f0s_p_scale0 .. 100
    default=10.0    		Size (precisely, "scale")
    float f0s_p_frc0 .. 100
    default=10.0    		Friction
    float f0s_p_ing0 .. 100
    default=10.0    		Ingestion
    float f0s_p_asm0 .. 100
    default=0.0    		AssimilationThe interpretation and influence of this property must be implemented by the experiment definition
    stnioJ :s0f :sciteneG
    float f0s_j_new0 .. 100
    default=5.0    		New joint
    float f0s_j_del0 .. 100
    default=5.0    		Delete joint
    float f0s_j_stm0 .. 100
    default=0.0    		StaminaThe interpretation and influence of this property must be implemented by the experiment definition
    float f0s_j_vred0 .. 100
    default=0.0    		Visual: red
    float f0s_j_vgrn0 .. 100
    default=0.0    		Visual: green
    float f0s_j_vblu0 .. 100
    default=0.0    		Visual: blue
    snorueN :s0f :sciteneG
    float f0s_n_new0 .. 100
    default=5.0    		New neuron
    float f0s_n_del0 .. 100
    default=5.0    		Delete neuron
    float f0s_n_prp0 .. 100
    default=10.0    		Change properties
    snoitcennoC :s0f :sciteneG
    float f0s_c_new0 .. 100
    default=5.0    		New connection
    float f0s_c_del0 .. 100
    default=5.0    		Delete connection
    float f0s_c_wei0 .. 100
    default=10.0    		Change weight
    1f :sciteneG
    int f1_xo_propor0 .. 1 (false/true)
    default=1    		Proportional crossoverCross over (exchange) corresponding segments of the two parent genotypes?

    f1 uses a two-point crossing over.
    If this option is turned on, cut points will be selected proportionally to neural genes in both parents, and a similar number of characters will be exchanged if possible.
    Thus, if both parents have the same number of neurons, then this will be preserved in their children.
    ygolohproM :1f :sciteneG
    float f1_smX0 .. 100
    default=4.0    		Add/remove a stick X
    float f1_smJunct0 .. 100
    default=1.0    		Add/remove a branch ( )
    float f1_smComma0 .. 100
    default=1.0    		Add/remove a comma ,
    float f1_smModif0 .. 100
    default=4.0    		Add/remove a modifierModifiers: LlRrCcQqFfMmEeWwSsAaIiDdGgBb
    string f1_mut_exmodExcluded modifiersModifiers that will not be added nor deleted during mutation
    (all: LlRrCcQqFfMmEeWwSsAaIiDdGgBb)
    ten norueN :1f :sciteneG
    float f1_nmNeu0 .. 100
    default=4.0    		Add/remove a neuronAdds a (connected) neuron or removes a neuron
    float f1_nmConn0 .. 100
    default=2.0    		Add/remove neural connection
    float f1_nmProp0 .. 100
    default=1.0    		Add/remove neuron property setting
    float f1_nmWei0 .. 100
    default=1.0    		Change connection weight
    float f1_nmVal0 .. 100
    default=1.0    		Change property value
    4f :sciteneG
    float f4_mut_add0 .. 100
    default=4.0    		Add nodeMutation: probability of adding a node
    float f4_mut_add_div0 .. 100
    default=4.0    		- add divisionAdd node mutation: probability of adding a division
    float f4_mut_add_conn0 .. 100
    default=1.0    		- add connectionAdd node mutation: probability of adding a neural connection
    float f4_mut_add_neupar0 .. 100
    default=1.0    		- add neuron propertyAdd node mutation: probability of adding a neuron property/modifier
    float f4_mut_add_rep0 .. 100
    default=1.0    		- add repetition '#'Add node mutation: probability of adding the '#' repetition gene
    float f4_mut_add_simp0 .. 100
    default=4.0    		- add simple nodeAdd node mutation: probability of adding a random, simple gene
    float f4_mut_del0 .. 100
    default=1.0    		Delete nodeMutation: probability of deleting a node
    float f4_mut_mod0 .. 100
    default=1.0    		Modify nodeMutation: probability of changing a node
    float f4_mut_modneu_conn0 .. 100
    default=3.0    		- neuron input: modify sourceNeuron input mutation: probability of changing its source neuron
    float f4_mut_modneu_weight0 .. 100
    default=3.0    		- neuron input: modify weightNeuron input mutation: probability of changing its weight
    int f4_mut_max_rep2 .. 20
    default=6    		Maximum number for '#' repetitionsMaximum allowed number of repetitions for the '#' repetition gene
    string f4_mut_exmodExcluded modifiersModifiers that will not be added nor deleted during mutation
    (all: LlRrCcQqFfMmEeWwSsAaIiDdGgBb)
    8f :sciteneG
    float f8_mut_chg_begin_arg0 .. 100
    default=7.0    		Change beginning argumentmutation: probability of changing a beginning argument
    float f8_mut_chg_arg0 .. 100
    default=7.0    		Change argumentmutation: probability of changing a production's argument
    float f8_mut_del_comm0 .. 100
    default=8.0    		Delete commandmutation: probability of deleting a command
    float f8_mut_insert_comm0 .. 100
    default=8.0    		Insert commandsmutation: probability of inserting commands
    float f8_mut_enc0 .. 100
    default=8.0    		Encapsulate commandsmutation: probability of encapsulating commands
    float f8_mut_chg_cond_sign0 .. 100
    default=7.0    		Change condition signmutation: probability of changing a condition sign
    float f8_mut_add_param0 .. 100
    default=8.0    		Add parametermutation: probability of adding a parameter to the production
    float f8_mut_add_cond0 .. 100
    default=8.0    		Add conditionmutation: probability of adding a condition to the subproduction
    float f8_mut_add_subprod0 .. 100
    default=8.0    		Add subproductionmutation: probability of adding a subproduction
    float f8_mut_chg_iter_number0 .. 100
    default=7.0    		Change iteration numbermutation: probability of changing a number of iterations
    float f8_mut_del_param0 .. 100
    default=8.0    		Delete parametermutation: probability of deleting a parameter
    float f8_mut_del_cond0 .. 100
    default=8.0    		Delete conditionmutation: probability of deleting a condition
    float f8_mut_add_loop0 .. 100
    default=0.0    		Add loopmutation: probability of adding a loop
    float f8_mut_del_loop0 .. 100
    default=0.0    		Delete loopmutation: probability of deleting a loop
    float f8_mut_del_prod0 .. 100
    default=8.0    		Delete productionmutation: probability of deleting a production
    9f :sciteneG
    float f9_mut0 .. 1
    default=0.0    		Mutation probabilityHow many genes should be mutated during a single mutation (1=all genes, 0.1=ten percent, 0=one gene)
    Ff :sciteneG
    float fF_xover0.5 .. 1
    default=0.5    		Inherited in linear mix crossover0.5 => children are averaged parents.
    0.8 => children are only 20% different from parents.
    1.0 => each child is identical to one parent (no crossover).
    nf :sciteneG
    float fn_xover0.5 .. 1
    default=0.9    		Fraction inherited in linear mix crossover0.5 => children are averaged parents.
    0.8 => children are only 20% different from parents.
    1.0 => each child is identical to one parent (no crossover).
    int fn_xover_random0 .. 1 (false/true)
    default=1    		Random fraction inherited in crossoverIf active, the amount of linear mix is random in each crossover operation, so the "Fraction inherited in linear mix crossover" parameter is ignored.
    string fn_mut_bound_lowLower bounds for mutationA vector of lower bounds (one real value for each variable)
    string fn_mut_bound_highHigher bounds for mutationA vector of higher bounds (one real value for each variable)
    string fn_mut_stddevStandard deviations for mutationA vector of standard deviations (one real value for each variable)
    int fn_mut_single_var0 .. 1 (false/true)
    default=0    		Mutate only a single variableIf active, only a single randomly selected variable will be mutated in each mutation operation. Otherwise all variables will be mutated.
    noitatuM :Bf :sciteneG
    float fB_mut_substitute0 .. 100
    default=1.0    		SubstitutionRelative probability of changing a single random character (or a neuron) in the genotype
    float fB_mut_insert0 .. 100
    default=3.0    		InsertionRelative probability of inserting a random character in a random place of the genotype
    float fB_mut_insert_neuron0 .. 100
    default=3.0    		Insertion of a neuronRelative probability of inserting a neuron in a random place of genotype
    float fB_mut_delete0 .. 100
    default=4.0    		DeletionRelative probability of deleting a random character (or a neuron) in the genotype
    float fB_mut_duplicate0 .. 100
    default=0.0    		DuplicationRelative probability of copying a single *gene* of the genotype and appending it to the beginning of this genotype
    float fB_mut_translocate0 .. 100
    default=4.0    		TranslocationRelative probability of swapping two substrings in the genotype
    revossorC :Bf :sciteneG
    float fB_cross_gene_transfer0 .. 100
    default=0.0    		Horizontal gene transferRelative probability of crossing over by copying a single random gene from each parent to the beginning of the other parent
    float fB_cross_crossover0 .. 100
    default=100.0    		Crossing overRelative probability of crossing over by a random distribution of genes from both parents to both children
    Hf :sciteneG
    float fH_mut_addition0 .. 100
    default=4.0    		Add elementProbability of adding a new element
    float fH_mut_add_joint0 .. 100
    default=4.0    		 - add jointProbability of adding a new stick handle
    float fH_mut_add_neuron0 .. 100
    default=3.0    		 - add neuronProbability of adding a new neuron handle
    float fH_mut_add_connection0 .. 100
    default=1.0    		 - add neural connectionProbability of adding a new neuron connection handle
    float fH_mut_deletion0 .. 100
    default=4.0    		Delete elementProbability of removing an element
    float fH_mut_handle0 .. 100
    default=1.0    		Modify vectors of handlesProbability of changing values in vectors of a handle
    float fH_mut_property0 .. 100
    default=4.0    		Modify properties of handlesProbability of changing properties of handles
    Lf :sciteneG
    int fL_maxdefinedwords0 .. 100
    default=10    		Maximum number of defined wordsMaximum number of words that can be defined in the L-System
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    float fL_axm_mut_prob0 .. 100
    default=4.0    		Axiom mutationProbability of performing mutation operations on axiom
    float fL_rul_mut_prob0 .. 100
    default=1.0    		Rule's successor mutationProbability of performing mutation operations on the successor of a random rule
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    float fL_mut_addition0 .. 100
    default=4.0    		Addition of a word to a sequenceProbability of adding a random existing word to the axiom or to one of successors
    float fL_mut_add_stick0 .. 100
    default=1.0    		 - addition of a stickProbability of adding a stick
    float fL_mut_add_neuro0 .. 100
    default=4.0    		 - addition of a neuronProbability of adding a neuron
    float fL_mut_add_conn0 .. 100
    default=4.0    		 - addition of a neuron connectionProbability of adding a neuron connection
    float fL_mut_add_rot0 .. 100
    default=2.0    		 - addition of rotation wordsProbability of adding one of rotation words
    float fL_mut_add_branch0 .. 100
    default=4.0    		 - addition of a branched stickProbability of adding a branch with a rotation and a stick
    float fL_mut_add_other0 .. 100
    default=1.0    		 - addition of defined wordsProbability of adding another word defined in the genotype
    float fL_mut_worddefaddition0 .. 100
    default=1.0    		Addition of a new word definitionProbability of adding a new word definition to the genotype
    float fL_mut_ruleaddition0 .. 100
    default=1.0    		Addition of a new rule definitionProbability of adding a new rule definition for an existing word
    float fL_mut_rulecond0 .. 100
    default=1.0    		Modification of a rule conditionProbability of modifying a random rule condition
    float fL_mut_changeword0 .. 100
    default=4.0    		Change a random wordProbability of changing a word name or a formula of a random word from an axiom or one of successors
    float fL_mut_changeword_formula0 .. 100
    default=4.0    		 - change of a formulaProbability of changing a formula in a word
    float fL_mut_changeword_name0 .. 100
    default=2.0    		 - change of a nameProbability of changing a name in a word
    float fL_mut_changeiter0 .. 100
    default=1.0    		Change the number of iterationsProbability of changing the number of iterations of the L-System
    float fL_mut_changeiter_step0 .. 1
    default=1.0    		Step of the iteration changeThe minimal step that should be used for changing iterations in the L-System
    float fL_mut_deletion0 .. 100
    default=4.0    		Deletion of a random wordProbability of deleting a random word from an axiom or a random successor (also deletes the rule if there is only one word in the successor)
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    float fS_mut_add_part0 .. 100
    default=10.0    		Add partmutation: probability of adding a part
    float fS_mut_rem_part0 .. 100
    default=10.0    		Remove partmutation: probability of deleting a part
    float fS_mut_mod_part0 .. 100
    default=10.0    		Modify partmutation: probability of changing the part type
    float fS_mut_change_joint0 .. 100
    default=10.0    		Change jointmutation: probability of changing a joint
    float fS_mut_add_param0 .. 100
    default=10.0    		Add parammutation: probability of adding a parameter
    float fS_mut_rem_param0 .. 100
    default=10.0    		Remove parammutation: probability of removing a parameter
    float fS_mut_mod_param0 .. 100
    default=10.0    		Modify parammutation: probability of modifying a parameter
    float fS_mut_mod_mod0 .. 100
    default=10.0    		Modify modifiermutation: probability of modifying a modifier
    float fS_mut_add_neuro0 .. 100
    default=10.0    		Add neuronmutation: probability of adding a neuron
    float fS_mut_rem_neuro0 .. 100
    default=10.0    		Remove neuronmutation: probability of removing a neuron
    float fS_mut_mod_neuro_conn0 .. 100
    default=10.0    		Modify neuron connectionmutation: probability of changing a neuron connection
    float fS_mut_add_neuro_conn0 .. 100
    default=10.0    		Add neuron connectionmutation: probability of adding a neuron connection
    float fS_mut_rem_neuro_conn0 .. 100
    default=10.0    		Remove neuron connectionmutation: probability of removing a neuron connection
    float fS_mut_mod_neuro_params0 .. 100
    default=10.0    		Modify neuron paramsmutation: probability of changing a neuron param
    int fS_circle_section0 .. 1 (false/true)
    default=1    		Ensure circle sectionEnsure that ellipsoids and cylinders have circle cross-section
    int fS_use_elli0 .. 1 (false/true)
    default=1    		Use ellipsoids in mutationsUse ellipsoids in mutations
    int fS_use_cub0 .. 1 (false/true)
    default=1    		Use cuboids in mutationsUse cuboids in mutations
    int fS_use_cyl0 .. 1 (false/true)
    default=1    		Use cylinders in mutationsUse cylinders in mutations
    int fS_mut_add_part_strong0 .. 1 (false/true)
    default=1    		Strong add part mutationAdd part mutation will produce more parametrized parts
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    function _propertyAdd(string id, string type_description, string name, int flags, string help_text)doesn't return a valueAdd property (id,type,name,help)Using most _property functions is restricted for internal purposes. Use "property:" or "state:" definitions in your script files to change object properties.
    function _propertyAddGroup(string name)doesn't return a valueAdd property groupUsing most _property functions is restricted for internal purposes. Use "property:" or "state:" definitions in your script files to change object properties.
    function _propertyChange(string id, string type_description, string name, int flags, string help_text)doesn't return a valueChange propertyUsing most _property functions is restricted for internal purposes. Use "property:" or "state:" definitions in your script files to change object properties.
    function _propertyClear()doesn't return a valueRemove all propertiesUsing most _property functions is restricted for internal purposes. Use "property:" or "state:" definitions in your script files to change object properties.
    function _propertyExists(string name)returns intCheck for property existence
    function _propertyRemove(int index)doesn't return a valueRemove propertyUsing most _property functions is restricted for internal purposes. Use "property:" or "state:" definitions in your script files to change object properties.
    function _propertyRemoveGroup(int index)doesn't return a valueRemove property groupUsing most _property functions is restricted for internal purposes. Use "property:" or "state:" definitions in your script files to change object properties.
    function crossOver(Geno, Geno)returns GenoCrossoverreturns crossed over genotype
    function getSimplest(string format)returns GenoGet simplest genotypereturns the simplest genotype for a given encoding (format). "0" means f0, "4" means f4, etc.
    function mutate(Geno)returns GenoMutatereturns mutated Geno object from supplied Geno
    function operReport()doesn't return a valueOperators reportShow available genetic operators
    function toHTML(string)returns stringHTMLize a genotypereturns genotype expressed as colored HTML
    function toHTMLshort(string)returns stringHTMLize a genotype, shorten if neededreturns genotype (abbreviated if needed) in colored HTML format
    function toLaTeX(string)returns stringLaTeXize a genotypereturns genotype in colored LaTeX format
    function validate(Geno)returns GenoValidatereturns validated (if possible) Geno object from supplied Geno
    Global context
    Experiment definition   Neuron definitions   Fitness formula   Visual style definition   Signal label formula   Command line interface   Framsticks Theater