ClassName= LearningParam    
    // Increase the importance of SOV and decrease importance of
    // encoding cost (compared to default)
    
    
    NetInitCenterWeight = 1.0e-5	 // keep sums centered on 0
    NetInitRangeWeight = 1.0e-7 // scale weights for desired variance on sums
    NetCenterDecay = 0.95
    NetRangeDecay =0.99
    
    NetResetAfter = 35
    
    QRBestCostMult=1.0	// was 0.5
    QRBestQMult = 1.0
    QRBestSOVMult = 0.5 // was 1.0

    NetActWrongWeight = 1.0 // was 1.2	 // extra weight for correcting wrong answers
    
    NetActChangeCorrectWeight = 1.0	 // extra weight for transitions
					 // where the correct answer changes
    ActPartialKluge =  0	// 0 is off, 1 is weight proportional to prob
    
    LayBaseTimesSeq = 0.001	// very slow learning
    LayMaxBaseRate = 0.01
    LayWeightOverBase = 1.00
    LayWeightOverBaseForMult = 1.5
    LayPseudoOverBase = 0.05	// was 0.05
    LayPseudoOverBaseForMult =0.1
    LayBiasOverBase = 0		// was 0.5
    LayBiasOverBaseForMult = 0.05
    LayGainOverBase = 0		// was 0.01
    LayGainOverBaseForMult = 0.01
    LayDesiredSqOverNumWeights = 0.06
    
    LayGainExtConst = 0		// turn off weight extinction
    LayBiasExtConst = 0
    LayPseudoExtConst = 0 	// turn off pseudocount extinction
    LayGainExtConstForMult = 0
    LayBiasExtConstForMult = 0
    LayPseudoExtConstForMult = 0
    
    LayWindowShapeExp = 0.1	// slight shaping to window

    LayMaxWeight=5.00
    LayMaxWeightChange=0.01
    LayMaxPseudo = 10.0
    LayMaxPseudoChange = 2.0
    
    LayMaxBias=10.0	 // old code limited bias to window size,
			 // which may be better
    LayMaxBiasChange=0.1
    
    LayMaxGain=2.0	 // keep gain in [1/MaxGain, MaxGain]
    LayMaxGainChange = 1.5	 // scale by [1/GainChange, GainChange]
    
    LayMainObjWeight= 1.0
    LayMainObjWeightForMult=1.0
    LayMainObjPseudo= 1.0
    LayMainObjPseudoForMult = 1.0
    
    LayMainObjBias=0.010
    LayMainObjBiasForMult=0.005
    
    LayMainObjGain = 1.0
    LayMainObjGainForMult =1.0
    
    LayMaxWeightRateFactor = 2.0
    LayMaxPseudoRateFactor = 2.0
    LayMaxBiasRateFactor = 1.1
    LayMaxGainRateFactor = 1.1
    
    LayWeightRateDecay=0.995
    LayPseudoRateDecay = 0.99
    LayBiasRateDecayForLowerCost = 1.01
    LayBiasRateDecayForHigherCost=0.88	
    LayGainRateDecayForLowerCost = 1.01 	
    LayGainRateDecayForHigherCost=0.7	
    
    LayRangeMult = 0.6
    LayRangeDenom = 0.4
    LayRangeMinForMult = 0.1
    
    LayTotalInitialPseudo = 1.0

EndClassName= LearningParam