Package teamwork :: Package multiagent :: Module pwlSimulation :: Class PWLSimulation

Class PWLSimulation

             object --+        
                      |        
                   dict --+    
                          |    
Multiagent.MultiagentSystem --+
                              |
                             PWLSimulation

Instance Methods

[hide private]

new empty dictionary

__init__(self, agents=None, observable=False)
Initializes a collection to contain the given list of agents

source code

initialize(self)
Do any necessary preparation before doing whatever

source code

Element

microstep(self, turns, hypothetical=False, explain=False, state=None, suggest=False)
Step forward by the action of the given entities

source code

dict

hypotheticalAct(self, actions, exp=None, state=None)
Computes the scenario changes that would result from a given action

source code

dict

getState(self)
Returns: a dictionary of 'state' and relationships of the current simulation state

source code

getDelta(self, actions, state, exp=None)
Computes the changes to the given state distribution that would result from a given action

source code

dict

applyDynamics(self, actions, state, exp=None)
Compute the effect of the given actions on the given state vector

source code

getEffect(self, action, key, vector, instantiate=True, debug=False)
Computes the effect of the given action on the given StateKey

source code

applyChanges(self, delta, current=None)
Applies the differential changes to this set of entities

source code

explainAction(self, actions)

source code

__xml__(self, dynamics=False)

source code

bool

parse(self, element, agentClass=<class teamwork.agent.lightweight.PWLAgent at 0x17f5e40>, societyClass=None)
Returns: False iff unable to load a specified society file source code

Inherited from Multiagent.MultiagentSystem: __str__, addMember, getMember, 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__

Instance Variables

[hide private]

str

societyFile
the location of the GenericSociety

Properties

[hide private]

Inherited from object: __class__

Method Details

[hide private]

init(self, agents=None, observable=False)
(Constructor)

source code

Initializes a collection to contain the given list of agents

Parameters:

agents - the fully-specified agents
observable (bool) - iff True, agents always maintain correct beliefs about the world
effects (Action→StateKey[]) - a table of features that actions affect, indexed by action, with each value being a list of keys

Returns: new empty dictionary

Overrides: object.__init__

initialize(self)

source code

Do any necessary preparation before doing whatever

Overrides: Multiagent.MultiagentSystem.initialize: (inherited documentation)

microstep(self, turns, hypothetical=False, explain=False, state=None, suggest=False)

source code

Step forward by the action of the given entities

Parameters:

turns (dict[]) - the agents to act next, each entry in the list should be a dictionary:
- name: the name of the agent to act
- choices: the list of possible options this agent can consider in this turn (defaults to the list of all possible actions if omitted, or if the list is empty)
- history: a dictionary of actions already performed (defaults to the built-in history of this simulation instance)
hypothetical (bool) - if True, then this is only a hypothetical microstep; otherwise, it is real (default is False)
explain (bool) - if True, then add an explanation to the result (default is False)
suggest (bool) - this is ignored

Returns: Element

XML results

hypotheticalAct(self, actions, exp=None, state=None)

source code

Computes the scenario changes that would result from a given action

Parameters:

actions (dict:str->Action[]) - dictionary of actions, where each entry is a list of Action instances, indexed by the name of the actor
exp (Document) - an optional partial explanation to expand upon

Returns: dict

the changes that would result from actions

state: the change to state, in the form of a Distribution over KeyedMatrix (suitable to pass to applyChanges)
agent: the change to the recursive beliefs of agent, as returned by preComStateEstimator

getState(self)

source code

Returns: dict: a dictionary of 'state' and relationships of the current simulation state

getDelta(self, actions, state, exp=None)

source code

Computes the changes to the given state distribution that would result from a given action

Parameters:

actions (dict:str->Action[]) - dictionary of actions, where each entry is a list of Action instances, indexed by the name of the actor
state (Distribution(KeyedMatrix)) - the initial state
exp (Document) - an optional partial explanation to expand upon