Update documentation of StochasticSearchIteartor functions

[nicolaefilat]

 Proposes a list of programs using the location provided by `neighbourhood` and the `dict`.
   
     propose(iter::T, current_program::RuleNode, neighbourhood_node_loc::NodeLoc, dmap::AbstractVector{Int}, dict::Union{Nothing,Dict{String,Any}}) where T <: StochasticSearchIterator -> Iter[RuleNode]
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 Based on the current program and possible cost and temperature it accepts the program or not. Usually we would always want to accept
 better programs but we might get stuck if we do so. That is why some implementations of the `accept` function accept with a probability 
 costs that are worse. 
 `cost` means how different are the outcomes of the program compared to the correct outcomes.
 The lower the `cost` the better the program performs on the examples. The `cost` is provided by the `cost_function`

    accept(::T, current_cost::Real, next_cost::Real, temperature::Real) where T <: StochasticSearchIterator -> Bool
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 Returns the new temperature based on the previous temperature. Higher the `temperature` means that the algorithm will explore more.
   
    temperature(::T, current_temperature::Real) where T <: StochasticSearchIterator -> Real
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 Returns the cost of the current program. It receives a list of tuples `(expected, found)` and gives back a cost.
   
     cost_function(outcomes::Tuple{<:Number,<:Number}[]) -> Real

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 # Fields

This function signatures no longer match the actual implementation