def __init__(self,
name='platform',
maxTask=1,
synchronous=False,
queueSystem=None,
settings=None,
logHandlers=[],
**kwargs):
# A platform can contains many queues
if queueSystem is None:
self.queue_system = QueueSystem()
else:
self.queue_system = queueSystem
self.settings = {'MAX_TASK':maxTask,
'SYNCHRONOUS':synchronous,
'OPTIONS':None}
if settings is not None:
self.settings.update(settings)
self.settings.update(kwargs)
# Running information
self.running = {}
self.task_id = 0
Agent.__init__(self, name=name, logHandlers=logHandlers)
self.message_handlers['inform-task-finish'] = self.finalize_task
self.message_handlers['cfp-cancel-queue'] = self.cancel_queue
return
def __init__(self,
name=None,
taskId=None,
command=None,
sessionTag=None,
input=None,
output='/dev/null',
logHandlers=[]):
'''
Each task object correspond to an application of the target
algorithm on a test problem.
'''
self.task_id = taskId # task_id is assigned by platform
self.command = command
self.output = output
if name is None:
Agent.__init__(self, name=command, logHandlers=logHandlers)
else:
Agent.__init__(self, name=name, logHandlers=logHandlers)
if sessionTag is None:
self.session_tag = self.name
else:
self.session_tag = sessionTag
return
def __init__(self,
name='platform',
maxTask=1,
synchronous=False,
queueSystem=None,
settings=None,
logHandlers=[],
**kwargs):
# A platform can contains many queues
if queueSystem is None:
self.queue_system = QueueSystem()
else:
self.queue_system = queueSystem
self.settings = {
'MAX_TASK': maxTask,
'SYNCHRONOUS': synchronous,
'OPTIONS': None
}
if settings is not None:
self.settings.update(settings)
self.settings.update(kwargs)
# Running information
self.running = {}
self.task_id = 0
Agent.__init__(self, name=name, logHandlers=logHandlers)
self.message_handlers['inform-task-finish'] = self.finalize_task
self.message_handlers['cfp-cancel-queue'] = self.cancel_queue
return
def __init__(self,
name=None,
taskId=None,
command=None,
sessionTag=None,
input=None,
output='/dev/null',
logHandlers=[]):
'''
Each task object correspond to an application of the target
algorithm on a test problem.
'''
self.task_id = taskId # task_id is assigned by platform
self.command = command
self.output = output
if name is None:
Agent.__init__(self, name=command, logHandlers=logHandlers)
else:
Agent.__init__(self, name=name, logHandlers=logHandlers)
if sessionTag is None:
self.session_tag = self.name
else:
self.session_tag = sessionTag
return
def __init__(self,
name='function evaluator',
function=None,
functionFile=None,
logHandlers=[],
**kwargs):
Agent.__init__(self,
name=name,
logHandlers=logHandlers)
if function is None:
if functionFile is not None:
# The model is loaded by pickling
# Be able to be serialized is a requirement for
# a model object
f = open(functionFile)
function = pickle.load(f)
f.close()
if function is None:
raise Exception("Error in creating an evaluator")
self.function = function
self.message_handlers['cfp-evaluate-point'] = self.evaluate
return
def test_multi_agent_framework():
from mafrw import Agent
from mafrw import Environment
agent = Agent()
env = Environment()
agent.register(env)
def test_multi_agent_framework():
from mafrw import Agent
from mafrw import Environment
agent = Agent()
env = Environment()
agent.register(env)
def __init__(self,
name='data manager',
rows=None,
columns=None,
storage=None,
logHandlers=[]):
self.file_name = 'data_storage.txt'
Agent.__init__(self, name=name, logHandlers=logHandlers)
self.message_handlers['inform-measure-values'] = self.add_data
self.message_handlers['cfp-collect'] = self.collect_data
return
def __init__(self,
name='data manager',
rows=None,
columns=None,
storage=None,
logHandlers=[]):
self.file_name = 'data_storage.txt'
Agent.__init__(self, name=name, logHandlers=logHandlers)
self.message_handlers['inform-measure-values'] = self.add_data
self.message_handlers['cfp-collect'] = self.collect_data
return
def __init__(self,
name='structure evaluator',
structure=None,
problems=None,
measures=None,
logHandlers=[],
**kwargs):
Agent.__init__(self,
name=name,
logHandlers=logHandlers)
self.structure = structure
# Data cache is a map from a parameter tag with an ExperimentResult
# object
self.data_cache = DataCache(name='data-cache',
problems=problems,
measures=measures)
self.message_handlers['inform-measure-values'] = self.evaluate
self.message_handlers['cfp-evaluate-parameter'] =
self.create_cache_entry
return
def __init__(self,
name='structure evaluator',
structure=None,
problems=None,
measures=None,
logHandlers=[],
**kwargs):
Agent.__init__(self,
name=name,
logHandlers=logHandlers)
self.structure = structure
# Data cache is a map from a parameter tag with an ExperimentResult
# object
self.data_cache = DataCache(name='data-cache',
problems=problems,
measures=measures)
self.message_handlers['inform-measure-values'] = self.evaluate
self.message_handlers['cfp-evaluate-parameter'] = \
self.create_cache_entry
return