params.yml

# This file contains all the credence-based parameters for full_calc.py
# (see also ./runtime_constants.py for params that just balance runtime and precision)

# Discussion of default values/what values should be is on this open Google doc:
# https://docs.google.com/document/d/1Ag_cnQLBAIzzSJEGos94KDsgvFFvCz-ML54wOZoY7A4/

# Uncomment time of perils fields prefixed with 'current_perils_' to affect the current time of perils only

preperils:
  preindustrial:
    # Parameters describing the chance of becoming industrial (vs extinct) from
    # a preindustrial state
    # Desmos graph of the probability of the xth civilisation going directly extinct
    # from a preindustrial state: https://www.desmos.com/calculator/d2uyrkresh
    # The Desmos values correspond to the parameters in this section as follow:
    # x = number of previous civilisations (calculated for every number up to the MAX_CIVILISATIONS constant)
    # a = per_civilisation_annual_extinction_probability_multiplier
    # b = annual_extinction_probability
    # c = base_expected_time_in_years
    # d = stretch_per_reboot

    base_expected_time_in_years: 10_571
    # base_expected_time_in_years: 476  # optimistic
    # base_expected_time_in_years: 285_714  # pessimistic
    stretch_per_reboot: 1.05

    base_annual_extinction_probability: 0.000012
    per_reboot_annual_extinction_probability_multiplier: 1.02

  industrial:
    # Parameters describing the chance of reaching a time of perils (vs going
    # extinct) from an industrial state
    # Desmos graph of the probability of the xth civilisation going directly extinct
    # from an industrial state:
    # https://www.desmos.com/calculator/2gzrlt4bfa
    # The Desmos values correspond to the parameters in this section as follow:
    # x = number of previous civilisations (calculated for every number up to the MAX_CIVILISATIONS constant)
    # a = per_civilisation_annual_extinction_probability_multiplier
    # b = annual_extinction_probability_denominator
    # c = base_expected_time_in_years
    # d = stretch_per_reboot
    # g = base_annual_extinction_probability_coefficient

    base_expected_time_in_years: 109 # ~geometric mean of the optimistic and pessimistic views
    # base_expected_time_in_years: 429 # pessimistic
    # base_expected_time_in_years: 29 # optimistic
    stretch_per_reboot: 3.5 # geometric mean of the optimistic and pessimistic views
    # stretch_per_reboot: 10 # pessimistic
    # stretch_per_reboot: 1.2 # optimistic

    base_annual_extinction_probability: 0.000012
    annual_extinction_probability_coefficient: 0.7 # Constant multiple of annual_extinction_probability
    per_reboot_annual_extinction_probability_multiplier: 1.02

perils:
  # Some of the parameters in 'perils' have a 'current_perils_'-prefixed
  # alternative.* If you uncomment this, they will be used only for determining
  # the graphs of our current time of perils, and the default values will be used
  # for all future times of perils.
  #
  # TODO At the moment, using any of these
  # current_perils parameters will mess up the alignment of later columns in the
  # CSV file by inserting a column for each current_perils value.

  # The time of perils graphs all assume k=0. To see
  # the effect of reboots on the estimates, you'll need to manually increase the x-stretch (parameter
  # b on Desmos) by an appropriate proportion.
  current_progress_year: 71

  extinction:
    # Desmos graph of the probability in progress year x of transitioning
    # from a perils state directly to extinction: https://www.desmos.com/calculator/zvt7dy6pwb
    # The Desmos values correspond to the parameters in this section as follows
    # x = progress year
    # a = y_scale
    # b = base_x_scale
    # c = x_translation
    # d = sharpness
    # m = per_civilisation_background_risk_numerator
    # n = base_background_risk_denominator

    # y_scale is the max annual probability of extinction from a time of perils.
    y_scale: 0.00054 # Optimistic/best guess (see Google doc for why optimistic guess is used by default)
    # y_scale: 0.004 # Pessimistic
    # y_scale: 0.0012 # the geometric mean of optimistic and pessimistic views
    # current_perils_y_scale: 0

    base_x_scale: 108 # The x-stretch of the graph at k=0 (primary determinant of how quickly the
    # extinction risk rises per progress year at low k-values).
    # current_perils_base_x_scale: 0

    # stretch_per_reboot is a per-reboot multiplier on the x-stretch (the formula for x_scale is
    # base_x_scale * stretch_per_reboot ** k), so the primary determinant of how quickly the
    # extinction risk rises per year at high k-values). Higher values imply longer before both good
    # and bad technology-caused exits from the time of perils become possible.
    stretch_per_reboot: 3.5 # ~the geometric mean of optimistic and pessimistic views
    # stretch_per_reboot: 10 # Pessimistic
    # stretch_per_reboot: 1.2 # Optimistic
    # current_perils_stretch_per_reboot: 0

    # x_translation is the delay at the start of a time of perils before we expect
    # this risk to kick in.
    x_translation: 15
    # current_perils_x_translation: 0

    # sharpness is an abstract (but not-very-influential parameter) codetermining steepness.
    sharpness: 6 #
    # current_perils_sharpness: 0

    # base_background_risk is the background risk (i.e. non-technologicalrisk ) of extinction, constant throughout
    # a given time of perils.
    base_background_risk: 0.0000054

    # per_reboot_background_risk_multiplier is a multiplier applied to base_background_risk
    # for each civilisation after the first. # Note that high values of this will break
    # the calculator, by making the per-year risk in later civilisations approach or exceed 1.
    # TODO: make it more robust to this
    per_reboot_background_risk_multiplier: 1.05

  preindustrial:
    # Desmos graph of the probability in progress year x of transitioning
    # from a perils state directly to a preindustrial state:
    # https://www.desmos.com/calculator/viekibtzhv
    # The Desmos values correspond to the parameters in this section as follows
    # x = progress year
    # a = y_scale
    # b = base_x_scale
    # c = x_translation
    # d = sharpness
    # m = per_civilisation_background_risk_numerator
    # n = base_background_risk_denominator

    y_scale: 0.0008
    # current_perils_y_scale: 0

    base_x_scale: 180
    # current_perils_base_x_scale: 0

    x_translation: 5
    # current_perils_x_translation: 0

    sharpness: 0.4
    # current_perils_sharpness: 0

    stretch_per_reboot: 3.5 # The geometric mean of upper and lower bounds
    # stretch_per_reboot: 10 # Pessimistic
    # stretch_per_reboot: 1.2 # Optimistic
    # current_perils_stretch_per_reboot: 0

    per_reboot_background_risk_multiplier: 1.05

    base_background_risk: 0.000016

  industrial:

    # Desmos graph of the probability in progress year x of transitioning
    # from a perils state directly to an industrial state:
    # https://www.desmos.com/calculator/ioo96u3cih
    # The Desmos values correspond to the parameters in this section as follows
    # x = progress year
    # a = y_scale
    # b = base_x_scale
    # c = x_translation
    # d = sharpness
    # m = per_civilisation_background_risk_numerator
    # n = base_background_risk_denominator

    y_scale: 0.0056 # Geometric mean of optimistic and pessimistic views
    # y_scale: 0.0015 # Optimistic
    # y_scale: 0.021 # Pessimistic
    # current_perils_y_scale: 0.0015

    base_x_scale: 180
    # current_perils_base_x_scale: 85

    # current_perils_x_translation: 0
    x_translation: 0 # The definitionally minimum possible regression at the start of a time of
    # perils

    sharpness: 0.9
    # current_perils_sharpness: 0.9

    stretch_per_reboot: 3.5 # Best guess: ~the geometric mean of optimistic and pessimistic views
    # stretch_per_reboot: 10 # Pessimistic
    # stretch_per_reboot: 1.2 # Optimistic
    # current_perils_stretch_per_reboot: 3.5

    per_reboot_background_risk_multiplier: 1.05
    base_background_risk: 0.000022

  progress_year_n:
    # Desmos graph of the probability of retrogressing
    # within a perils state from progress year p to progress year n (n = x):
    # https://www.desmos.com/calculator/xmjhulo4lj The three graphs represent the
    # three algorithms described below Green is the exponential algorithm, blue
    # the linear algorithm, red is the mean of the two.
    # The Desmos values correspond to the parameters in this section as follows
    # x = target progress year (iterated through in the code)
    # a = any_regression
    # p = origin progress year (iterated through in code), such that 0 <= x <= p
    # n = regression_size_skew

    # algorithm: 'exponential' # Optimistic
    # algorithm: 'linear' # Pessimistic
    algorithm: 'mean' # Since much of the runtime comes from the algorithm used here,
    # consider setting it to one of the more efficient ones above if an upper/lower bound will do

    regression_size_skew: 1.4 # Only required for exponential and mean algorithms (but
    # messes up the results.csv columning if you comment it out when using linear)
    any_regression: 0.057



  multiplanetary:
    # Desmos graph of the probability in progress year x of transitioning
    # from a perils state directly to a multiplanetary state: https://www.desmos.com/calculator/sbkmcbfzlj
    # The Desmos values correspond to the parameters in this section as follows
    # x = progress year
    # a = y_scale
    # b = base_x_scale
    # c = x_translation
    # d = sharpness

    y_scale: 0.07
    # current_perils_y_stretch: 0

    base_x_scale: 240
    # current_perils_base_x_scale: 0

    x_translation: 70
    # current_perils_x_translation: 0

    sharpness: 1.5
    # current_perils_sharpness: 0

    stretch_per_reboot: 3.5 # Geometric mean of optimistic and pessimistic views
    # stretch_per_reboot: 10 # Pessimistic
    # stretch_per_reboot: 1.2 # Optimistic
    # current_perils_stretch_per_reboot: 3.5

    # I'm including the subsequent two params to simplify the code, but these should
    # remain unchanged for normal use cases - the 'background' risk of humanity
    # becoming multiplanetary is probably safe to treat as 0.
    per_reboot_background_risk_multiplier: 0
    base_background_risk: 0


  interstellar:
    # No Desmos graph since by default I give this 0 probability. I assume this
    # can only happen directly from the time of perils (without
    # going via a multiplanetary state) via a benevolent AI singleton. My sense
    # is that AI predictions mostly fall into either Camp A: 'it's going to be
    # an overwhelmingly powerful new force of nature that will very likely
    # kill us all' and Camp B: 'it's going to be a very powerful tool which
    # doesn't fundamentally change human dynamics'. On either view, this
    # transition seems very unlikely, though not inconceivable. For simplicity's
    # sake, I'm treating this transition as as 0 probability (y-stretch of
    # 0 with everything else being irrelevant), but you can adjust if that seems
    # wrong.

    # Some values below are set to 1 to avoid Division by Zero errors in the code

    # current_perils_y_scale: 0
    y_scale: 0
    # current_perils_base_x_scale: 118
    base_x_scale: 1
    stretch_per_reboot: 1
    # current_perils_x_translation: 15
    x_translation: 0
    # current_perils_sharpness: 2
    sharpness: 0
    # current_perils_stretch_per_reboot: 10

    # I'm including the subsequent two params to simplify the code, but these should
    # be 0 under normal assumptions.

    # You could set them higher to factor in the chance
    # of an alien civilisation spreading throughout the galaxy - though then you'd need to tweak
    # the other states to allow for that too, and it would probably easier to just model separately.
    per_reboot_background_risk_multiplier: 0
    base_background_risk: 0

multiplanetary:
  extinction:
    # Desmos graph of the probability of transitioning from x 'planets' (self
    # supporting, technologically independent settlements) directly to extinction
    # https://www.desmos.com/calculator/d4iu3jsyfa
    # The Desmos values correspond to the parameters in this section as follows
    # x = number of planets (calculated for every number up to the MAX_PLANETS constant)
    # a = two_planet_risk
    # b = decay_rate
    # c = x_translation
    # d = min_risk

    two_planet_risk: 0.12 # The probability of this transition from 2 planets
    decay_rate: 0.45 # the proportion by which risk for an n-planet civilisation
    # decreases for an (n+1)-planet civilisation
    min_risk: 0
    stretch_per_reboot: 1


  preindustrial:
    # By default I treat the probability of transitioning to a preindustrial state as 0 on
    # the grounds that it seems such a precise amount of damage to a multiplanetary
    # civilisation that it's not worth the computation/complexity costs. If you
    # disagree, then you’ll need to provide values for the next two parameters.
    two_planet_risk: 0
    decay_rate: 0
    min_risk: 0
    stretch_per_reboot: 1

  industrial:
    # While this looks somewhat more plausible than transitioning to preindustrial,
    # it still seems so much more specific than an event which either wipes out
    # humanity or leaves the remainder with some advanced technology as to be
    # treatable as 0
    two_planet_risk: 0
    decay_rate: 0
    min_risk: 0
    stretch_per_reboot: 1

  n_planets:
    # Desmos graph of the probability of transitioning from x 'planets' (self
    # supporting, technologically independent settlements) to q planets (1 <= q < x)
    # https://www.desmos.com/calculator/qr4vkbtijs
    # Graph with the the emphasis flipped, i.e. the probability of transitioning from q to x planets:
    # https://www.desmos.com/calculator/ycerxpiz0k
    # In both graphs the probability of any regression is itself
    # a function of number of planets (allowing the optimistic view that over time
    # humans will become less likely to blow ourselves up) . Unlike in the time
    # of perils, a 'regression' must be a loss of at
    # least 1, and at most (x-1), since regressing to 0 planets is covered by 'extinction'.
    #
    # On both graphs the black line indicates the probability that, given a
    # regression from <x or n> we regress to <n or x> planets respectively.

    # The green line represents the total probability after multiplying by the
    # probability of any regression that we regress the given number of planets.
    two_planet_risk: 0.2
    decay_rate: 0.4

    # min_risk is the minimum risk of losing at least one planet before gaining
    # one in an arbitrarily large civilisation.
    min_risk: 0 # Optimistic
    # min_risk: 0.04 # Pessimistic


    regression_size_skew: 1.4

    # TODO MD->SC: I would invert this param because it's confusing that a
    # larger number means fewer planets.
    stretch_per_reboot: 1

  perils: n/a
  # transitioning to perils is just the specific case of transitioning to n=1 planets.

  interstellar:

    # Desmos graph of the probability of transitioning from x 'planets' (self
    # supporting, technologically independent settlements) directly to an
    # interstellar state: https://www.desmos.com/calculator/r5c6cqwlux
    # The Desmos values correspond to the parameters in this section as follows
    # x = number of planets (calculated for every number up to the MAX_PLANETS constant)
    # a = two_planet_risk
    # b = decay_rate
    # c = x_translation
    # d = min_risk

    # (unlike the other multiplanetary transitions, this uses the s-curve formula)
    y_scale: 0.65
    base_x_scale: 13
    sharpness: 2
    stretch_per_reboot: 1