# Copyright 2006 by Sean Luke and George Mason University
# Licensed under the Academic Free License version 3.0
# See the file "LICENSE" for more information

parent.0 = framsticks.params

# When eval.masterproblem is turned on, the system assumes
# use of the master/slave evaluator.
eval.masterproblem = ec.eval.MasterProblem

# Turning this on will provide synchronization
# information for debugging the master/slave evaluator
eval.masterproblem.debug-info = true

# How large should each slave's job queue be?  ECJ will
# keep slaves' TCP/IP streams filled with jobs even if the
# slaves haven't processed them yet, which has a significant
# effect on network performance.  Increasing this number is
# likely to be more efficient.  Note that once a job is
# committed to a slave, a brand new slave coming on-line cannot
# take it -- it'll have to sit and wait, which isn't particularly
# efficient.  At the very least, it's probably helpful to have 2
# or 3 jobs in the queue.
eval.masterproblem.max-jobs-per-slave = 3

# How large should our job be?  If you're doing ordinary
# non-coevolutionary evolution, you can specify how many individuals
# should be placed into a job (maximum) and sent to the slave
# to be evaluated at one time, using the below parameter.
# If your individuals are small in size, this can significantly
# improve the network bandwidth.  If the individuals are large
# in size, it'll have no real effect.  Furthermore, if your
# slave is running in 'evolve' mode, this parameter will determine
# the maximum (and typical) size of the "population" the slave is
# evolving.  This works for both steady-state and generational evolution,
# but if you're doing coevolution, the job size is ignored -- instead
# the job will consist of the individuals to be coevolved together.
eval.masterproblem.job-size = 2

# This defines the socket port that the master listens in
# for incomoing Slaves to connect.
eval.master.port = 15000