SamplingInverseUtilityFunction

class negmas.preferences.SamplingInverseUtilityFunction(ufun, max_samples_per_call=10000)

Bases: negmas.preferences.protocols.InverseUFun

A utility function inverter that uses sampling.

Nothing is done during initialization so the fixed cost of this inverter is minimal. Nevertheless, each time the system is asked to find an outcome within some range, it uses random sampling which is very inefficient and suffers from the curse of dimensinality.

Attributes Summary

initialized
ufun

Methods Summary

__call__(rng, normalized)	Calling an inverse ufun directly is equivalent to calling one_in()
all(rng)	Finds all outcomes with in the given utility value range
best()	Finds the best outcome
best_in(rng, normalized)	Finds an outcome with highest utility within the given range
extreme_outcomes()	Finds the worst and best outcomes that can be returned.
init()	Used to intialize the inverse ufun.
max()	Finds the maximum utility value that can be returned.
min()	Finds the minimum utility value that can be returned.
minmax()	Finds the minimum and maximum utility values that can be returned.
one_in(rng, normalized)	Finds an outcmoe with the given utility value.
some(rng, normalized[, n])	Finds some outcomes with the given utility value (if discrete, all)
within_fractions(rng)	Finds outocmes within the given fractions of utility values.
within_indices(rng)	Finds outocmes within the given indices with the best at index 0 and the worst at largest index.
worst()	Finds the worst outcome
worst_in(rng, normalized)	Finds an outcome with lowest utility within the given range

Attributes Documentation

initialized: bool

ufun: UFun

Methods Documentation

__call__(rng, normalized)

Calling an inverse ufun directly is equivalent to calling one_in()

Return type

Outcome | None

all(rng)

Finds all outcomes with in the given utility value range

Parameters

rng (float | tuple[float, float]) – The range. If a value, outcome utilities must match it exactly

Remarks:

• If issues or outcomes are not None, then init_inverse will be called first

• If the outcome-space is discrete, this method will return all outcomes in the given range

Return type

list[Outcome]

abstract best()

Finds the best outcome

Return type

tuple

best_in(rng, normalized)

Finds an outcome with highest utility within the given range

Parameters

• rng (float | tuple[float, float]) – The range (or single value) of utility values to search for outcomes

• normalized (bool) – if True, the input rng will be understood as ranging from 0-1 (1=max, 0=min) independent of the ufun actual range

Return type

Outcome | None

extreme_outcomes()

Finds the worst and best outcomes that can be returned.

Remarks:

These may be different from the results of ufun.extreme_outcomes() as they can be approximate.

Return type

tuple[tuple, tuple]

init()

Used to intialize the inverse ufun. Any computationally expensive initialization should be done here not in the constructor.

abstract max()

Finds the maximum utility value that can be returned.

Remarks:

• May be different from the maximum of the whole ufun if there is approximation

Return type

float

abstract min()

Finds the minimum utility value that can be returned.

Remarks:

• May be different from the minimum of the whole ufun if there is approximation

Return type

float

minmax()

Finds the minimum and maximum utility values that can be returned.

Remarks:

These may be different from the results of ufun.minmax() as they can be approximate.

Return type

tuple[float, float]

one_in(rng, normalized)

Finds an outcmoe with the given utility value.

Parameters

• rng (float | tuple[float, float]) – The range (or single value) of utility values to search for outcomes

• normalized (float) – if True, the input rng will be understood as ranging from 0-1 (1=max, 0=min) independent of the ufun actual range

Return type

Outcome | None

some(rng, normalized, n=None)

Finds some outcomes with the given utility value (if discrete, all)

Parameters

• rng (float | tuple[float, float]) – The range. If a value, outcome utilities must match it exactly

• n (int | None) – The maximum number of outcomes to return

Remarks:

• If issues or outcomes are not None, then init_inverse will be called first

• If the outcome-space is discrete, this method will return all outcomes in the given range

Return type

list[Outcome]

abstract within_fractions(rng)

Finds outocmes within the given fractions of utility values. rng is always assumed to be normalized between 0-1

Return type

list[tuple]

abstract within_indices(rng)

Finds outocmes within the given indices with the best at index 0 and the worst at largest index.

Remarks:

• Works only for discrete outcome spaces

Return type

list[tuple]

abstract worst()

Finds the worst outcome

Return type

tuple

worst_in(rng, normalized)

Finds an outcome with lowest utility within the given range

Parameters

• rng (float | tuple[float, float]) – The range (or single value) of utility values to search for outcomes

• normalized (bool) – if True, the input rng will be understood as ranging from 0-1 (1=max, 0=min) independent of the ufun actual range

Return type

Outcome | None