	-----CONVERGENCE-----
beta=0.01			% If KL sum updates are less than Beta * Alpha
elitesConvergence=true			% If the distribution can converge when the elites grow too large.
numUpdatesConverged=10.0			% If KL sum updates remain below Beta for this many updates
slotFixing=false			% If slots can be fixed.

	-----EVALUATION-----
experimentMode=false			% If GUI elements are to be hidden.
loadAgentObservations=true			% If agent observations should be loaded from file ever.
onlineTesting=false			% If greedy testing in an online fashion.
performanceEpisodeGap=10.0			% The gap between measuring performances
policyRepeats=3.0			% Number of times policy is repeated
policyTestingSize=100.0			% Size of average performance sliding window
saveExperimentFiles=false			% If module files should be saved into sub-directories so they aren't loaded in successive runs.
systemOutput=true			% If the console should output data during execution.
test=false			% If just running tests
testBestPolicy=true			% If the best elite policy should be used for testing, else uses greedy generator.
testIterations=100.0			% Number of iterations to test the final testing for

	-----SAMPLING-----
confidenceInterval=3.0			% The amount of confidence for sampling every element at least once.
elitesFunction=3.0			% The size of the elites: 0=Av # rules, 1=Sum slot means, 2=Sum # KL rules, 3=Max KL weighted rules, 4=Confidence * Max KL weighted rules * num slots * rho
elitesMultiple=1.0			% The multiplier of the elites size.
globalElites=false			% If elites remain in the set forever
initialSlotMean=0.5			% The initial slot mu probabilities.
initialSlotOrderingSD=0.25			% The SD of the slot order
retestStale=false			% If stale policies should be immediately retested.
seedModuleRules=false			% If module rules should just be loaded & seeded _once_.
splitInitially=true			% If the slots should be split at the beginning of learning
useGeneralModules=false			% If using/learning general modules
useModules=false			% If using/learning modules

	-----SPECIALISATION-----
dynamicSlots=true			% If the slots grow dynamically
inheritParent=false			% If newly created slots inherit mu(S) and o(S) of the parent slot.
numNumericalSplits=3.0			% The number of numerical splits
onlyGoalRules=false			% If the agent should only create rules with the goal condition in it
onlySplitProbable=false			% If only high mu(S) slots should split
slotThreshold=0.5			% The slot splitting threshold. -1 means use |S|-1 threshold
splitBuffer=0.1			% The final proportion of episodes which disallow slot splitting.
usingUnbound=false			% If using unbound variables instead of anonymous variables.
widerSpecialisation=false			% If including non-action specialisation conditions

	-----UPDATING-----
alpha=0.6			% Step size update
boundedElites=true			% If the minimum number of elites = Max KL weighted rules.
earlyUpdating=true			% If the algorithm should perform updates using incomplete, but viable, elites.
localAlpha=true			% If updates are performed slot locally
negativeUpdates=false			% If performing negative updates
populationUpdates=false			% If updates are performed in an online fashion, or population-based.
resetElites=false			% If the entire elites are reset when a new slot is created.
resetSlotCount=false			% Resets the update counter in the slot after splitting.
rho=0.05			% N_E's proportion of N
