def eval(self, offer: Optional["Outcome"]) -> Optional[UtilityValue]:
if offer is None:
return self.reserved_value
if self.issue_utilities is None:
raise ValueError(
"No issue utilities were set. Call set_params() or use the constructor"
)
u = {}
for k in ikeys(self.issue_utilities):
v = iget(offer, k)
u[k] = gmap(iget(self.issue_utilities, k), v)
return self.f(u)
def xml(self, issues: List[Issue]) -> str:
output = ""
keys = list(ikeys(issues))
for i, k in enumerate(keys):
issue_name = iget(issues, k).name
output += f'<issue index="{i+1}" etype="discrete" type="discrete" vtype="discrete" name="{issue_name}">\n'
vals = iget(issues, k).all
for indx, u in enumerate(vals):
output += (
f' <item index="{indx+1}" value="{u}" evaluation="{u}" />\n'
)
output += "</issue>\n"
for i, k in enumerate(keys):
output += (
f'<weight index="{i+1}" value="{iget(self.weights, k)}">\n</weight>\n'
)
return output
def eval(self, offer: Optional["Outcome"]) -> Optional[UtilityValue]:
if offer is None:
return self.reserved_value
u = ExactUtilityValue(0.0)
for k in ikeys(self.issue_utilities):
if isinstance(offer, tuple):
v = iget(offer, self.issue_indices[k])
else:
v = iget(offer, k)
current_utility = gmap(iget(self.issue_utilities, k), v)
if current_utility is None:
return None
w = iget(self.weights, k) # type: ignore
if w is None:
return None
try:
u += w * current_utility
except FloatingPointError:
continue
return u
def eval(self, offer: Optional["Outcome"]) -> Optional[UtilityValue]:
if offer is None:
return self.reserved_value
# offer = outcome_for(offer, self.ami) if self.ami is not None else offer
u = ExactUtilityValue(0.0)
if isinstance(self.weights, dict):
if isinstance(offer, dict):
for k, w in self.weights.items():
u += w * (iget(offer, k, self.missing_value) +
self.biases.get(k, 0))
return u
else:
if self.ami is not None:
newoffer = dict()
for i, v in enumerate(offer):
newoffer[self.ami.issues[i].name] = v
elif self.issue_names is not None:
newoffer = dict()
for i, v in enumerate(offer):
newoffer[self.issue_names[i]] = v
elif self.issues is not None:
newoffer = dict()
for i, v in enumerate(offer):
newoffer[self.issues[i].name] = v
else:
raise ValueError(
f"Cannot find issue names but weights are given as a dict."
)
for k, w in self.weights.items():
u += w * (iget(offer, k, self.missing_value) +
self.biases.get(k, 0))
return u
offer = outcome_as_tuple(offer)
return sum(w * (v + b)
for w, b, v in zip(self.weights, self.biases, offer))
def __init__(
self,
outcomes: Iterable["Outcome"],
distributions: Iterable["UtilityDistribution"] = None,
issue_names: Iterable[str] = None,
name=None,
reserved_value: UtilityValue = float("-inf"),
ami: AgentMechanismInterface = None,
outcome_type: Optional[Type] = None,
id=None,
):
super().__init__(
name=name,
outcome_type=outcome_type,
reserved_value=reserved_value,
ami=ami,
id=id,
)
outcomes, distributions = (
list(outcomes),
(list(distributions) if distributions is not None else None),
)
if len(outcomes) < 1:
raise ValueError(
"IPUtilityFunction cannot be initialized with zero outcomes")
self.tupelized = False
self.n_issues = len(outcomes[0])
if issue_names is None:
self.issue_names = sorted(ikeys(outcomes[0]))
else:
self.issue_names = range(len(outcomes[0]))
self.issue_keys = dict(zip(range(self.n_issues), self.issue_names))
if not isinstance(outcomes[0], tuple):
outcomes = [
tuple(iget(_, key, None) for key in self.issue_names)
for _ in outcomes
]
self.tupelized = True
if distributions is None:
distributions = [
UtilityDistribution(dtype="uniform", loc=0.0, scale=1.0)
for _ in range(len(outcomes))
]
self.distributions = dict(zip(outcomes, distributions))
def xml(self, issues: List[Issue]) -> str:
"""Generates an XML string representing the utility function
Args:
issues:
Examples:
>>> from negmas.utilities.nonlinear import MappingUtilityFunction
>>> issues = [Issue(values=10, name='i1'), Issue(values=['delivered', 'not delivered'], name='i2')
... , Issue(values=4, name='i3')]
>>> f = LinearUtilityAggregationFunction([lambda x: 2.0*x
... , {'delivered': 10, 'not delivered': -10}
... , MappingUtilityFunction(lambda x: x-3)]
... , weights=[1.0, 2.0, 4.0])
>>> print(f.xml(issues))
<issue index="1" etype="discrete" type="discrete" vtype="discrete" name="i1">
<item index="1" value="0" evaluation="0.0" />
<item index="2" value="1" evaluation="2.0" />
<item index="3" value="2" evaluation="4.0" />
<item index="4" value="3" evaluation="6.0" />
<item index="5" value="4" evaluation="8.0" />
<item index="6" value="5" evaluation="10.0" />
<item index="7" value="6" evaluation="12.0" />
<item index="8" value="7" evaluation="14.0" />
<item index="9" value="8" evaluation="16.0" />
<item index="10" value="9" evaluation="18.0" />
</issue>
<issue index="2" etype="discrete" type="discrete" vtype="discrete" name="i2">
<item index="1" value="delivered" evaluation="10" />
<item index="2" value="not delivered" evaluation="-10" />
</issue>
<issue index="3" etype="discrete" type="discrete" vtype="discrete" name="i3">
<item index="1" value="0" evaluation="-3" />
<item index="2" value="1" evaluation="-2" />
<item index="3" value="2" evaluation="-1" />
<item index="4" value="3" evaluation="0" />
</issue>
<weight index="1" value="1.0">
</weight>
<weight index="2" value="2.0">
</weight>
<weight index="3" value="4.0">
</weight>
<BLANKLINE>
>>> print(f.xml({i:_ for i, _ in enumerate(issues)}))
<issue index="1" etype="discrete" type="discrete" vtype="discrete" name="i1">
<item index="1" value="0" evaluation="0.0" />
<item index="2" value="1" evaluation="2.0" />
<item index="3" value="2" evaluation="4.0" />
<item index="4" value="3" evaluation="6.0" />
<item index="5" value="4" evaluation="8.0" />
<item index="6" value="5" evaluation="10.0" />
<item index="7" value="6" evaluation="12.0" />
<item index="8" value="7" evaluation="14.0" />
<item index="9" value="8" evaluation="16.0" />
<item index="10" value="9" evaluation="18.0" />
</issue>
<issue index="2" etype="discrete" type="discrete" vtype="discrete" name="i2">
<item index="1" value="delivered" evaluation="10" />
<item index="2" value="not delivered" evaluation="-10" />
</issue>
<issue index="3" etype="discrete" type="discrete" vtype="discrete" name="i3">
<item index="1" value="0" evaluation="-3" />
<item index="2" value="1" evaluation="-2" />
<item index="3" value="2" evaluation="-1" />
<item index="4" value="3" evaluation="0" />
</issue>
<weight index="1" value="1.0">
</weight>
<weight index="2" value="2.0">
</weight>
<weight index="3" value="4.0">
</weight>
<BLANKLINE>
"""
output = ""
keys = list(ikeys(issues))
for i, k in enumerate(keys):
issue = iget(issues, k)
issue_name = issue.name
if issue.is_float():
output += f'<issue index="{i + 1}" etype="real" type="real" vtype="real" name="{issue_name}">\n'
output += f'<range lowerbound = {issue.min_value} upperbound = {issue.max_value} ></range>'
# elif issue.is_integer():
# output += f'<issue index="{i + 1}" etype="integer" type="integer" vtype="integer" name="{issue_name}">\n'
# output += f'<range lowerbound = {issue.min_value} upperbound = {issue.max_value} ></range>'
else:
output += f'<issue index="{i+1}" etype="discrete" type="discrete" vtype="discrete" name="{issue_name}">\n'
vals = iget(issues, k).all
for indx, v in enumerate(vals):
try:
u = gmap(iget(self.issue_utilities, issue_name), v)
except:
u = gmap(iget(self.issue_utilities, k), v)
v_ = (v
if not (isinstance(v, tuple) or isinstance(v, list))
else "-".join([str(_) for _ in v]))
output += (
f' <item index="{indx+1}" value="{v_}" evaluation="{u}" />\n'
)
output += "</issue>\n"
if isinstance(issues, dict):
if isinstance(self.weights, dict):
weights = self.weights
else:
weights = {k: v for k, v in zip(ikeys(issues), self.weights)}
else:
if isinstance(self.weights, list):
weights = self.weights
else:
weights = list(self.weights.get(i.name, 1.0) for i in issues)
for i, k in enumerate(keys):
output += f'<weight index="{i+1}" value="{iget(weights, k)}">\n</weight>\n'
return output
def xml(self, issues: List[Issue]) -> str:
"""Generates an XML string representing the utility function
Args:
issues:
Examples:
>>> issues = [Issue(values=10, name='i1'), Issue(values=4, name='i2')]
>>> f = LinearUtilityFunction(weights=[1.0, 4.0])
>>> print(f.xml(issues))
<issue index="1" etype="discrete" type="discrete" vtype="discrete" name="i1">
<item index="1" value="0" evaluation="0" />
<item index="2" value="1" evaluation="1" />
<item index="3" value="2" evaluation="2" />
<item index="4" value="3" evaluation="3" />
<item index="5" value="4" evaluation="4" />
<item index="6" value="5" evaluation="5" />
<item index="7" value="6" evaluation="6" />
<item index="8" value="7" evaluation="7" />
<item index="9" value="8" evaluation="8" />
<item index="10" value="9" evaluation="9" />
</issue>
<issue index="2" etype="discrete" type="discrete" vtype="discrete" name="i2">
<item index="1" value="0" evaluation="0" />
<item index="2" value="1" evaluation="1" />
<item index="3" value="2" evaluation="2" />
<item index="4" value="3" evaluation="3" />
</issue>
<weight index="1" value="1.0">
</weight>
<weight index="2" value="4.0">
</weight>
<BLANKLINE>
"""
output = ""
keys = list(ikeys(issues))
for i, k in enumerate(keys):
issue = iget(issues, k)
issue_name = issue.name
if issue.is_float():
output += f'<issue index="{i + 1}" etype="real" type="real" vtype="real" name="{issue_name}">\n'
output += f'<range lowerbound = {issue.min_value} upperbound = {issue.max_value} ></range>'
# elif issue.is_integer():
# output += f'<issue index="{i + 1}" etype="integer" type="integer" vtype="integer" name="{issue_name}">\n'
# output += f'<range lowerbound = {issue.min_value} upperbound = {issue.max_value} ></range>'
else:
output += f'<issue index="{i+1}" etype="discrete" type="discrete" vtype="discrete" name="{issue_name}">\n'
vals = iget(issues, k).all
bias = iget(self.biases, k, 0.0)
for indx, u in enumerate(vals):
uu = issue.value_type(u + bias)
output += f' <item index="{indx+1}" value="{uu}" evaluation="{u}" />\n'
output += "</issue>\n"
if isinstance(issues, dict):
if isinstance(self.weights, dict):
weights = self.weights
else:
weights = {k: v for k, v in zip(ikeys(issues), self.weights)}
else:
if isinstance(self.weights, list) or isinstance(
self.weights, tuple):
weights = list(self.weights)
else:
weights = list(self.weights.get(i.name, 1.0) for i in issues)
for i, k in enumerate(keys):
output += f'<weight index="{i+1}" value="{iget(weights, k)}">\n</weight>\n'
return output
def xml(self, issues: List[Issue]) -> str:
"""Represents the function as XML
Args:
issues:
Examples:
>>> f = HyperRectangleUtilityFunction(outcome_ranges=[
... {0: (1.0, 2.0), 1: (1.0, 2.0)},
... {0: (1.4, 2.0), 2: (2.0, 3.0)}]
... , utilities= [2.0, 9.0 + 4.0])
>>> print(f.xml([Issue((0.0, 4.0), name='0'), Issue((0.0, 9.0), name='1')
... , Issue((0.0, 9.0), name='2')]).strip())
<issue index="1" name="0" vtype="real" type="real" etype="real">
<range lowerbound="0.0" upperbound="4.0"></range>
</issue><issue index="2" name="1" vtype="real" type="real" etype="real">
<range lowerbound="0.0" upperbound="9.0"></range>
</issue><issue index="3" name="2" vtype="real" type="real" etype="real">
<range lowerbound="0.0" upperbound="9.0"></range>
</issue><utility_function maxutility="-1.0">
<ufun type="PlainUfun" weight="1" aggregation="sum">
<hyperRectangle utility_function="2.0">
<INCLUDES index="0" min="1.0" max="2.0" />
<INCLUDES index="1" min="1.0" max="2.0" />
</hyperRectangle>
<hyperRectangle utility_function="13.0">
<INCLUDES index="0" min="1.4" max="2.0" />
<INCLUDES index="2" min="2.0" max="3.0" />
</hyperRectangle>
</ufun>
</utility_function>
"""
output = ""
for i, issue in enumerate(ivalues(issues)):
name = issue.name
if isinstance(issue.values, tuple):
output += (
f'<issue index="{i+1}" name="{name}" vtype="real" type="real" etype="real">\n'
f' <range lowerbound="{issue.values[0]}" upperbound="{issue.values[1]}"></range>\n'
f"</issue>")
elif isinstance(issue.values, int):
output += (
f'<issue index="{i+1}" name="{name}" vtype="integer" type="integer" etype="integer" '
f'lowerbound="0" upperbound="{issue.values - 1}"/>\n')
else:
output += (
f'<issue index="{i+1}" name="{name}" vtype="integer" type="integer" etype="integer" '
f'lowerbound="{min(issue.values)}" upperbound="{max(issue.values)}"/>\n'
)
# todo find the real maxutility
output += '<utility_function maxutility="-1.0">\n <ufun type="PlainUfun" weight="1" aggregation="sum">\n'
for rect, u, w in zip(self.outcome_ranges, self.mappings,
self.weights):
output += f' <hyperRectangle utility_function="{u * w}">\n'
for indx in ikeys(rect):
values = iget(rect, indx, None)
if values is None:
continue
if isinstance(values, float) or isinstance(values, int):
mn, mx = values, values
elif isinstance(values, tuple):
mn, mx = values
else:
mn, mx = min(values), max(values)
output += (
f' <INCLUDES index="{indx}" min="{mn}" max="{mx}" />\n'
)
output += f" </hyperRectangle>\n"
output += " </ufun>\n</utility_function>"
return output