---PROGRAM ARGUMENTS---
	-----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=true			% -----MODIFIED----- % If GUI elements are to be hidden.
loadAgentObservations=false			% -----MODIFIED----- % 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=true			% -----MODIFIED----- % If module files should be saved into sub-directories so they aren't loaded in successive runs.
systemOutput=false			% -----MODIFIED----- % If the console should output data during execution.
test=false			% If just running tests
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 = |D_S|.
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
onlineUpdates=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
-----------------------
GOAL (unstack): (forall (block ?A) (clear ?A))

Episode	Average	SD	Min	Max	Elite-Average	Elite-SD	NumSlots	Slots-SD	NumRules	Rules-SD
10	0.1305555544793606	0.20994234389674465	0.0	0.0833333358168602	0.3333333343267441	0.4714045207910317	5.0	0.0	24.0	0.0
20	0.13698413372039794	0.11902069251253729	0.0	0.15079365670681	0.6488888978958129	0.37167178856835115	5.0	0.0	24.0	0.0
30	0.17466666921973228	0.09761602924174197	0.10000000149011612	0.10000000149011612	0.9822222232818604	0.05621826616323453	5.0	0.0	24.0	0.0
40	0.19336996972560883	0.08751258661006973	0.15018315613269806	0.09890110790729523	0.9666666686534882	0.10540924905606476	5.0	0.0	24.0	0.0
50	0.20088235810399055	0.09067989662236922	0.15931373834609985	0.1200980395078659	0.9777777791023254	0.07027283270404318	5.0	0.0	24.0	0.0
60	0.18400000371038913	0.08428054462525998	0.15000000596046448	0.10000000149011612	1.0	0.0	5.0	0.0	24.0	0.0
70	0.20456387400627135	0.08741499521948182	0.17149758338928223	0.14251208305358887	1.0	0.0	5.0	0.0	24.0	0.0
80	0.20505329072475434	0.08176852232939705	0.1875593513250351	0.1747388392686844	1.0	0.0	5.0	0.0	24.0	0.0
90	0.20562963373959064	0.08151080859787767	0.20000000298023224	0.1666666716337204	1.0	0.0	5.0	0.0	24.0	0.0
100	0.22217106223106384	0.079046080536625	0.23104575276374817	0.1598336398601532	1.0	0.0	5.0	0.0	24.0	0.0
110	0.2210808053612709	0.07582807369526842	0.210035040974617	0.1909409463405609	1.0	0.0	5.0	0.0	24.0	0.0
120	0.21847222223877907	0.07750893313238146	0.19249999523162842	0.17499999701976776	1.0	0.0	5.0	0.0	24.0	0.0
130	0.21856843680143356	0.06614478791213806	0.2007928192615509	0.16913320124149323	1.0	0.0	5.0	0.0	24.0	0.0
140	0.21728423610329628	0.06841082003498555	0.18644773960113525	0.17144618928432465	1.0	0.0	5.0	0.0	24.0	0.0
150	0.220777777582407	0.06913181015641262	0.17399999499320984	0.18000000715255737	1.0	0.0	5.0	0.0	24.0	0.0
160	0.2277548097074032	0.07198340423577905	0.1818891167640686	0.1875145584344864	1.0	0.0	5.0	0.0	24.0	0.0
170	0.23034524843096732	0.0690139820710865	0.18883667886257172	0.21177944540977478	1.0	0.0	5.0	0.0	24.0	0.0
180	0.23712962940335275	0.06761606890026962	0.1783333271741867	0.21666666865348816	1.0	0.0	5.0	0.0	24.0	0.0
190	0.24147698059678077	0.0657504197434329	0.18474702537059784	0.21048280596733093	1.0	0.0	5.0	0.0	24.0	0.0
200	0.24541895166039468	0.0609282839234807	0.200459823012352	0.22501131892204285	1.0	0.0	5.0	0.0	24.0	0.0
210	0.25182539969682693	0.0565060551590607	0.19571428000926971	0.22857142984867096	1.0	0.0	5.0	0.0	24.0	0.0
220	0.2590052396059036	0.05346830494838999	0.20496730506420135	0.2318277209997177	1.0	0.0	5.0	0.0	24.0	0.0
230	0.2694896966218948	0.05219148113540741	0.2308783233165741	0.23479151725769043	1.0	0.0	5.0	0.0	24.0	0.0
240	0.2822222262620926	0.05087961833282832	0.2462500035762787	0.23749999701976776	1.0	0.0	5.0	0.0	24.0	0.0
250	0.28402964025735855	0.05090336016574894	0.25237616896629333	0.2520080506801605	1.0	0.0	5.0	0.0	24.0	0.0
260	0.28986852914094924	0.049167908801306726	0.2580548822879791	0.2538537085056305	1.0	0.0	5.0	0.0	24.0	0.0
270	0.297191359102726	0.04785096468505756	0.2633333206176758	0.25555557012557983	1.0	0.0	5.0	0.0	24.0	0.0
280	0.3005059614777565	0.051544051866572176	0.27536413073539734	0.2571493983268738	1.0	0.0	5.0	0.0	24.0	0.0
290	0.3118537783622742	0.051209820555806605	0.2830863296985626	0.26549971103668213	1.0	0.0	5.0	0.0	24.0	0.0
300	0.3204722195863724	0.052077006967143305	0.28700000047683716	0.2800000011920929	1.0	0.0	5.0	0.0	24.0	0.0
310	0.3348055571317673	0.04952176980118407	0.31033334136009216	0.30000001192092896	1.0	0.0	5.0	0.0	24.0	0.0
320	0.3511611133813858	0.04822712725506839	0.343666672706604	0.3100000023841858	1.0	0.0	5.0	0.0	24.0	0.0
330	0.36800556182861327	0.051457669020562063	0.367000013589859	0.3400000035762787	1.0	0.0	5.0	0.0	24.0	0.0
340	0.3840055525302887	0.047446730598908214	0.3803333342075348	0.36666667461395264	1.0	0.0	5.0	0.0	24.0	0.0
350	0.4022833347320557	0.04494017088119801	0.40700000524520874	0.3700000047683716	1.0	0.0	5.0	0.0	24.0	0.0
360	0.419283327460289	0.04716385616832804	0.4269999861717224	0.3799999952316284	1.0	0.0	5.0	0.0	24.0	0.0
370	0.4313574075698853	0.05120260068904855	0.4403333365917206	0.36666667461395264	1.0	0.0	5.0	0.0	24.0	0.0
380	0.4513944387435913	0.056178234390153486	0.45366665720939636	0.3700000047683716	1.0	0.0	5.0	0.0	24.0	0.0
390	0.4663944453001022	0.059707164017371174	0.47699999809265137	0.3799999952316284	1.0	0.0	5.1	0.31622776601683794	24.0	0.0
400	0.48102777600288393	0.057670258693568496	0.47999998927116394	0.4099999964237213	1.0	0.0	5.1	0.31622776601683794	24.0	0.0
410	0.498416668176651	0.053412376726582195	0.49666666984558105	0.4166666567325592	1.0	0.0	5.1	0.31622776601683794	24.0	0.0
420	0.5162777692079544	0.05848116592574902	0.5099999904632568	0.4399999976158142	1.0	0.0	5.1	0.31622776601683794	24.0	0.0
430	0.5322777807712555	0.06254255650541124	0.5333333015441895	0.46000000834465027	1.0	0.0	5.1	0.31622776601683794	24.0	0.0
440	0.550277778506279	0.06079350770517821	0.5666666626930237	0.476666659116745	1.0	0.0	5.1	0.31622776601683794	24.0	0.0
450	0.5680555582046509	0.06334550624487861	0.597777783870697	0.5	1.0	0.0	5.1	0.31622776601683794	24.0	0.0
460	0.5816388845443725	0.06276554700871093	0.6077777743339539	0.5199999809265137	1.0	0.0	5.1	0.31622776601683794	24.0	0.0
470	0.596638885140419	0.06190982152418396	0.6244444251060486	0.5205555558204651	1.0	0.0	5.1	0.31622776601683794	24.0	0.0
480	0.6112500011920929	0.056933715294359276	0.647777795791626	0.5308333039283752	1.0	0.0	5.2	0.42163702135578385	24.0	0.0
490	0.6269166648387909	0.05745733245369863	0.6611111164093018	0.5575000047683716	1.0	0.0	5.2	0.42163702135578385	24.0	0.0
500	0.6419166624546051	0.059631997057503175	0.6577777862548828	0.5674999952316284	1.0	0.0	5.3	0.48304589153964794	24.0	0.0
510	0.6522499918937683	0.055437905630791616	0.6877777576446533	0.590833306312561	1.0	0.0	5.4	0.5163977794943222	24.0	0.0
520	0.667294442653656	0.05083267882246632	0.7044444680213928	0.6041666865348816	1.0	0.0	5.4	0.5163977794943222	24.0	0.0
530	0.6800722241401672	0.047550325719811326	0.7044444680213928	0.6274999976158142	1.0	0.0	5.4	0.5163977794943222	24.0	0.0
540	0.6849055469036103	0.05228365689435155	0.7177777886390686	0.6508333086967468	1.0	0.0	5.4	0.5163977794943222	24.0	0.0
550	0.704322224855423	0.04957171152854911	0.7377777695655823	0.6641666889190674	1.0	0.0	5.4	0.5163977794943222	24.0	0.0
560	0.7184611141681672	0.04572853571471407	0.757777750492096	0.6875	1.0	0.0	5.466666650772095	0.501848428101155	24.0	0.0
570	0.7322111189365387	0.04705341967608318	0.7777777910232544	0.7108333110809326	1.0	0.0	5.5	0.5270462766947299	24.0	0.0
580	0.7485444486141205	0.046293289528592206	0.7711111307144165	0.73416668176651	1.0	0.0	5.5	0.5270462766947299	24.0	0.0
590	0.7588777780532837	0.04519950211036474	0.7777777910232544	0.7508333325386047	1.0	0.0	5.5666666507720945	0.4981447024871624	24.0	0.0
600	0.7712111055850983	0.04385215839632437	0.7977777719497681	0.7608333230018616	1.0	0.0	5.6	0.5163977794943222	24.0	0.0
610	0.7798777759075165	0.049255525576939935	0.8077777624130249	0.7508333325386047	1.0	0.0	5.6	0.5163977794943222	24.0	0.0
620	0.7896185159683228	0.044214420660351264	0.8077777624130249	0.7674999833106995	1.0	0.0	5.766666650772095	0.4172218565777729	24.0	0.0
630	0.7933222234249115	0.044907660071354716	0.8077777624130249	0.7708333134651184	1.0	0.0	5.8	0.4216370213557839	24.0	0.0
640	0.8013222217559814	0.04530035718976034	0.8177777528762817	0.7741666436195374	1.0	0.0	5.8	0.4216370213557839	24.0	0.0
650	0.8070444464683533	0.04597432273078767	0.8177777528762817	0.7975000143051147	1.0	0.0	5.8	0.4216370213557839	24.0	0.0
660	0.8314333319664001	0.058786765262007844	0.875	0.8208333253860474	1.0	0.0	5.8	0.4216370213557839	24.0	0.0
670	0.8358499944210053	0.058150528530815065	0.875	0.8449999690055847	1.0	0.0	5.8	0.4216370213557839	24.0	0.0
680	0.841183340549469	0.060002494898867664	0.875	0.8616666793823242	1.0	0.0	5.8	0.4216370213557839	24.0	0.0
690	0.8479611217975617	0.05987945145559606	0.875	0.871666669845581	1.0	0.0	5.9	0.31622776601683794	24.0	0.0
700	0.8506277799606323	0.06261957710474014	0.875	0.871666669845581	1.0	0.0	5.9	0.31622776601683794	24.0	0.0
710	0.8586555600166321	0.06284353518677044	0.875	0.8816666603088379	1.0	0.0	5.9	0.31622776601683794	24.0	0.0
720	0.8645444452762604	0.058390047570080386	0.875	0.8816666603088379	1.0	0.0	5.9	0.31622776601683794	24.0	0.0
730	0.8680999934673309	0.05241813918992394	0.875	0.8816666603088379	1.0	0.0	5.9	0.31622776601683794	24.0	0.0
740	0.8737666666507721	0.0487111887601355	0.875	0.8916666507720947	1.0	0.0	5.9	0.31622776601683794	24.0	0.0
750	0.8784333288669586	0.04969137262939265	0.875	0.8916666507720947	1.0	0.0	5.9	0.31622776601683794	24.0	0.0
760	0.8810999929904938	0.04564713393593962	0.875	0.8849999904632568	1.0	0.0	5.9	0.31622776601683794	24.0	0.0
770	0.8837111055850982	0.04384109060034802	0.875	0.8977777361869812	1.0	0.0	5.9	0.31622776601683794	24.0	0.0
780	0.8873500108718873	0.041326445379623426	0.875	0.9108333587646484	1.0	0.0	5.9	0.31622776601683794	24.0	0.0
790	0.9025833308696747	0.03411456497123357	0.875	0.9041666388511658	1.0	0.0	5.9	0.31622776601683794	24.0	0.0
800	0.9052500009536744	0.0320566825493255	0.875	0.9108333587646484	1.0	0.0	5.9	0.31622776601683794	24.0	0.0
810	0.9072499990463256	0.029780703338141305	0.875	0.9108333587646484	1.0	0.0	5.9	0.31622776601683794	24.0	0.0
820	0.9109444439411163	0.028606522922150896	0.875	0.9108333587646484	1.0	0.0	5.9	0.31622776601683794	24.0	0.0
830	0.9159999966621399	0.03637468206728312	0.875	0.9008333086967468	1.0	0.0	5.9	0.31622776601683794	24.0	0.0
840	0.9179999947547912	0.03441800520417798	0.875	0.9008333086967468	1.0	0.0	5.9	0.31622776601683794	24.0	0.0
850	0.9276666641235352	0.03979461709691339	0.875	0.9900000095367432	1.0	0.0	5.9	0.31622776601683794	24.0	0.0
860	0.9291666686534882	0.038801491769130544	0.875	0.9900000095367432	1.0	0.0	5.9	0.31622776601683794	24.0	0.0
870	0.9291666686534882	0.038801491769130544	0.875	0.9900000095367432	1.0	0.0	5.9	0.31622776601683794	24.0	0.0
880	0.9291666686534882	0.038801491769130544	0.875	0.9900000095367432	1.0	0.0	5.9	0.31622776601683794	24.0	0.0
890	0.9291666686534882	0.038801491769130544	0.875	0.9900000095367432	1.0	0.0	5.9	0.31622776601683794	24.0	0.0
900	0.9291666686534882	0.038801491769130544	0.875	0.9900000095367432	1.0	0.0	5.9	0.31622776601683794	24.0	0.0
910	0.9291666686534882	0.038801491769130544	0.875	0.9900000095367432	1.0	0.0	5.9	0.31622776601683794	24.0	0.0
920	0.9287592649459839	0.039257685444588374	0.875	0.9900000095367432	1.0	0.0	5.9	0.31622776601683794	24.0	0.0
930	0.9290555596351624	0.038922208376773765	0.875	0.9900000095367432	1.0	0.0	5.9	0.31622776601683794	24.0	0.0
940	0.9290555596351624	0.038922208376773765	0.875	0.9900000095367432	1.0	0.0	5.9	0.31622776601683794	24.0	0.0
950	0.9297222256660461	0.03824062969752082	0.875	0.9900000095367432	1.0	0.0	5.9	0.31622776601683794	24.0	0.0
960	0.9297222256660461	0.03824062969752082	0.875	0.9900000095367432	1.0	0.0	5.9	0.31622776601683794	24.0	0.0
970	0.9297222256660461	0.03824062969752082	0.875	0.9900000095367432	1.0	0.0	5.9	0.31622776601683794	24.0	0.0
980	0.9297222256660461	0.03824062969752082	0.875	0.9900000095367432	1.0	0.0	5.9	0.31622776601683794	24.0	0.0
990	0.9312777817249298	0.0370701709510372	0.875	0.9900000095367432	1.0	0.0	5.9	0.31622776601683794	24.0	0.0
1000	0.9332777798175812	0.03649623752082638	0.875	0.9900000095367432	1.0	0.0	5.9	0.31622776601683794	24.0	0.0
1010	0.9332777798175812	0.03649623752082638	0.875	0.9900000095367432	1.0	0.0	5.9	0.31622776601683794	24.0	0.0
1020	0.9342777788639068	0.036617812405643116	0.875	0.9900000095367432	1.0	0.0	5.9	0.31622776601683794	24.0	0.0
1030	0.9342777788639068	0.036617812405643116	0.875	0.9900000095367432	1.0	0.0	5.9	0.31622776601683794	24.0	0.0
1040	0.9349444508552551	0.03684971309908358	0.875	0.9900000095367432	1.0	0.0	5.9	0.31622776601683794	24.0	0.0
1050	0.9380000054836273	0.03936651375903089	0.875	0.9900000095367432	1.0	0.0	5.9	0.31622776601683794	24.0	0.0
1060	0.9380000054836273	0.03936651375903089	0.875	0.9900000095367432	1.0	0.0	5.9	0.31622776601683794	24.0	0.0
Average Run Time: 0:0:4

Average episode length: 785.4 +- 116.60017152646046

Average num slots: 0.0 +- 0.0
