new empty dictionary
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__init__(self,
entities=[ ] )
Initializes a simulation to contain the given list of agents. |
source code
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KeyedVector
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applyDefaults(self,
progress=None,
total=None,
doBeliefs=True)
Applies the relevant generic models to the member agent models |
source code
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applyOrder(self,
entities=None)
Applies any generic society's order specification to this scenario |
source code
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microstep(self,
turns=[ ] ,
hypothetical=False,
explain=False,
suggest=False,
debug=Debugger (0))
Step forward by the action of the given entities |
source code
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Agent
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dict
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performMsg(self,
msg,
sender,
receivers,
hearers=[ ] ,
debug=Debugger (0),
explain=False)
Updates the scenario in response to the specified message |
source code
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updateAll(self,
action,
debug=Debugger (0))
Obsolete, still here for backward compatibility |
source code
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compileDynamics(self,
progress=None,
total=100,
profile=False)
Pre-compiles all of the dynamics trees for these agents |
source code
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PWLDynamics
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getDynamics(self,
actionDict,
lock=None,
debug=False)
Returns the overall dynamics function over the provided actions |
source code
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dict
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verifyTree(self,
tree,
validKeys=None,
errors=None)
Identifies and removes any extraneous keys in the given matrices |
source code
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getDynamicsMatrix(self,
worlds,
lookup)
Generates matrix representations of probabilistic dynamics, given the
space of possible worlds |
source code
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dict
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hypotheticalAct(self,
actions,
beliefs=None,
debug=Debugger (0))
Computes the scenario changes that would result from a given action |
source code
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__updateAgent(self,
entity,
actions,
delta,
lock,
world,
debug) |
source code
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performAct(self,
actions,
debug=Debugger (0))
Updates all of the entities in response to the given actions |
source code
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applyChanges(self,
delta,
descend=True,
rewind=False,
beliefs=None)
Applies the differential changes to this set of entities |
source code
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KeyedVector[]
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reachable(self,
horizon,
reachable=None,
states=None)
Generates the possible real-world states reachable from the current
states |
source code
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dict,dict
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generateWorlds(self,
level=0,
maxSize=100,
worlds=None)
Generates the space of possible n-level worlds within the
current simulation |
source code
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explainEffect(self,
actions,
effect={ } ,
prefix=None) |
source code
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explainDecision(self,
actor,
explanation)
Extracts explanation from explanation structure |
source code
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explainMessage(self,
name,
explanation)
Extracts explanation from message acceptance explanation structure |
source code
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(str,str,str)[]
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Document
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suggestAll(self,
actor,
option)
Generates alternative beliefs that might change the given action into
one that satisfies all objectives |
source code
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dict[]
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suggest(self,
actor,
action,
objective)
Suggest alternative beliefs that might change the given action into
one that satisfies the given objective |
source code
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Inherited from Simulation.MultiagentSimulation :
actionCount ,
activeMembers ,
actorCount ,
applyTurn ,
createTurnDynamics ,
deleteState ,
generateActions ,
generateOrder ,
getSequence ,
getState ,
getStateKeys ,
initializeOrder ,
next ,
updateTurn
Inherited from Multiagent.MultiagentSystem :
__str__ ,
members ,
save
Inherited from dict :
__cmp__ ,
__contains__ ,
__delitem__ ,
__eq__ ,
__ge__ ,
__getattribute__ ,
__getitem__ ,
__gt__ ,
__hash__ ,
__iter__ ,
__le__ ,
__len__ ,
__lt__ ,
__ne__ ,
__new__ ,
__repr__ ,
__setitem__ ,
clear ,
copy ,
fromkeys ,
get ,
has_key ,
items ,
iteritems ,
iterkeys ,
itervalues ,
keys ,
pop ,
popitem ,
setdefault ,
update ,
values
Inherited from object :
__delattr__ ,
__reduce__ ,
__reduce_ex__ ,
__setattr__
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