# Parameters describing a LazyLav execution
# Please preserve the order

# Environment parameters
OSVERS=stretch
LOGBACK_VERSION=1.2.3
JPATH=lib/lazylav/ll.jar:lib/slf4j/logback-classic-${LOGBACK_VERSION}.jar:lib/slf4j/logback-core-${LOGBACK_VERSION}.jar:.

LLHASH=6edb6ab1e77240dec68475d1263707f2086b22f3

# Experiment parameters
DESIGNDATE=20201001
DATE=20201001
LABEL=${DATE}-DOLA
NAME=${LABEL}
PERFORMER="Yasser Bourahla"
NBAGENTS="2,5,10,20,40"
RATIO="0.2"
NBCLSS="2"
SRATIO="0.2"
SCORING="1"
NBFEATURES="16"
NBITERATIONS=40000
NBRUNS=5
TARGETCLASS="0,1,2,3,4,5,6"
TESTSETPROP="0.1"
TESTSET="0,1,2,3,4,5,6,7,8,9"
LOADENVDIR="../input/zoology"
ORG=godecisions
DIRPREF=results


OPT="-DloadEnvDir=${LOADENVDIR} -DtargetClass=${TARGETCLASS} -DtestSetProp=${TESTSETPROP} -DtestSet=${TESTSET} -Dorganiser=${ORG} -DnumberOfFeatures=${NBFEATURES} -Dratio=${RATIO} -DnumberOfAgents=${NBAGENTS} -DnbIterations=${NBITERATIONS} -DnbRuns=${NBRUNS} -DnumberOfClasses=${NBCLSS} -DsampleRatio=${SRATIO} -Dscoring=${SCORING}"




# Documentation parameters

VARIATIONOF=20200623-DOLA

HYPOTHESIS="here there is no hypotheses, the goal is to situate how much agents improve compared to AMAIL"

EXPE="Agent adapt ontologies to agree on decision taking"
#
SETTING="Agents learn decision trees (transformed into ontologies); get income from environment; adapt by splitting their leaf nodes; environment generated from dataset"


# Would be better automated
#CLASSES="Population, PopulatedARExperiment, PopulationAlignmentAdjustingAgent, NOOEnvironment, ActionLogger, AverageLogger, Monitor"

# DEFAULT VALUES
DESIGNER="Yasser Bourahla"
EXPERIMENTER=${PERFORMER}
ANALYST=${PERFORMER}