def getAverageFitness(self):
"""
INPUT : None
OUTPUT : Returns the current avegare of the fitness value
of all the agents in the session.
DESCRIPTION : Self explanatory from OUTPUT
This function is used to get the average fitness value of
agents in the current session, this uses daemon functions
getCurrGen, getAgent
"""
try:
totalFitness = 0
currGen = daemon.getCurrGen(self)
for agentID in currGen:
totalFitness += daemon.getAgent(self, agentID).fitness
except Exception as e:
print(
"gaDisc.getAverageFitness failed with error as : {}".format(e))
totalFitness = 0
return (totalFitness / self.agentCount)
def getBestAgent(self):
"""
INPUT : None
OUTPUT : Returns the Agent with the best fitness value
at present , and None on error
DESCRIPTION : Self explanatory from OUTPUT
This is used to retrieve the best agent in the current
pool of agents based on their fitness value with
higher fitness corresponding to being better
uses daemon functions getCurrGen, getAgent
"""
try:
bestAgent = None
currGen = daemon.getCurrGen(self)
for agentID in currGen:
agent = daemon.getAgent(self, agentID)
if ((bestAgent is None)
or (bestAgent.fitness < agent.fitness)):
bestAgent = agent
except Exception as e:
print("gaDisc.getBestAgent failed with error as : {}".format(e))
bestAgent = None
return (bestAgent)
def getAgent(self, agentID):
"""
INPUT : AgentID
OUTPUT : Returns the agent with the given AgentId,
None on error
DESCRIPTION : Self explanatory from OUTPUT
"""
try:
agentObj = daemon.getAgent(self, agentID)
return (agentObj)
except Exception as e:
print("gaDisc.getAgent failed with error as : {}".format(e))
return (None)
def createNextGen(self):
"""
INPUT : None
OUTPUT : Returns 1 on success, None on failure
DESCRIPTION : Creates the next generation based on the session
conf that is set in the beginning of the session
This is the main attraction in this session file XD
the algorithm follows as this :
a 'numberOfSurvivors' number is selected randomly between
5 - 10 % of the population size. These many top agents will
qualify for next generation.
now, 1 % of the agents from the unselected agents pool is selected
in random and made to come into the survivor agents group as
wildcard entry
all the unselected agents are deleted (killed ?)
now the current population is used to create new children
by calling a daemon function aSexualRep, which returns a
new agentObj as a child when a parent agentObj is sent
this new child-agentObj will inherit the fitness value and
slightly modified from its parent, (Needs optimisation).
"""
try:
if (self.survival > 0.95):
survivalPerc = 0.95
numberOfSurvivors = int(
((self.survival + 0.05 * random.random()) * self.agentCount))
if (numberOfSurvivors < 1):
numberOfSurvivors = 1
listOfAgents = [(agent.agentID, agent.fitness) for agent in [
daemon.getAgent(self, agentID)
for agentID in daemon.getCurrGen(self)
]]
listOfAgents.sort(key=lambda x: x[1], reverse=True)
unselected = listOfAgents[numberOfSurvivors:]
# wildcard zero
wildCardEntries = random.sample(unselected,
int(len(unselected) * 0.00))
finalUnselected = [
agent for agent in unselected if (agent not in wildCardEntries)
]
for agent in finalUnselected:
daemon.deleteAgent(self, agent[0])
currPop = list(daemon.getCurrGen(self))
itr = 0
while (len(daemon.getCurrGen(self)) < self.agentCount):
if (self.generateMode == 'A'):
self.updateAgent(
daemon.aSexualRep(self, self.getAgent(currPop[itr])))
else:
self.updateAgent(
daemon.sexualRep(
self, self.getAgent(currPop[itr]),
self.getAgent(currPop[(itr + 1) %
(len(currPop))])))
itr = (itr + 1) % (len(currPop))
except Exception as e:
print("gaDisc.createNextGen failed with error as : {}".format(e))