anchor.diff:  ann_norm_single_input(I) -> I/256.0.
   
   ann_norm_sample_output(AggregatedOutputVector, _QOS) ->
  -    Fac = case norm(AggregatedOutputVector) of
  -        0.0 ->      0.0;
  -        0 ->        0.0;
  -        Norm ->     1.0 / Norm
  -    end,
  -    Fun = fun(W) -> Fac * W end,  % Same vector length of 1 for all samples
  +    Fun = fun(0) -> 0; ({N,S}) -> S/N end, 
       lists:map(Fun, AggregatedOutputVector). 
  +
  +% ann_norm_sample_output(AggregatedOutputVector, _QOS) ->
  +%     Fac = case norm(AggregatedOutputVector) of
  +%         0.0 ->      0.0;
  +%         0 ->        0.0;
  +%         Norm ->     1.0 / Norm
  +%     end,
  +%     Fun = fun(W) -> Fac * W end,  % Same vector length of 1 for all samples
  +%     lists:map(Fun, AggregatedOutputVector). 
   
   % ann_norm_sample_output(AggregatedOutputVector, _QOS) ->
   %   Fac = 1.0 / norm(AggregatedOutputVector),
  
positive.code:     ?ANN_OUTPUT_TARGET * Score * (BoardSize-MTE+1) / (BoardSize-?ANN_OUTPUT_MTE).
  
  vector_add(OldOut, Output) ->
      [Old + Out || {Old, Out} <- lists:zip(OldOut, Output)].
  
  ann_norm_input(L) -> [ann_norm_single_input(I) || I <- L].
  
  
negative.code: 
  %% Format a single sample for ann use (Board size input vector, Board size output vector)
  %% and aggregate into the training table using an input hash
  ann_sample_single(GameTypeId, Board, Move, Score, MTE) ->
      #egGameType{params=#{width:=Width, height:=Height, gravity:=Gravity, periodic:=Periodic}} = egambo_game:read_type(GameTypeId),
      {Input, Sym} = egambo_tictac_sym:norm(Width, Height, Gravity, Periodic, Board),
      Gain = ann_sample_gain(length(Input), Score, MTE),
      Move1 = Move + 1,           % one based index of move
      F = fun(I) -> 
          Inp=lists:nth(I, Input), 
          if 
              I==Move1 -> {1, Gain};   % move taken in sample
              Inp==32 ->  {0, 0};      % alternative legal move, not taken here
              true ->     0            % illegal move (occupied)
          end 
      end, 
      Output = lists:map(F, lists:seq(1, length(Input))),
  