This is extremely intesting domain. I feel that even more interesting topic than optimizing code would be in generating code to replicate a process based on input / output samples.
1, 2, 4, ?
(Dovetailer: for all n from 0 up, for all m from 0 to n, treat m as a Turing machine and run it for n steps. If it halts, yield its output.)
can you recommend some decision theory reading? Maybe more on a practical side?
Eisenführ/Weber/Langer: Rational Decision Making. Springer 2010. This is a good practical introduction in the standard methodology.
Keeney/Raiffa: Decisions with Multiple Objectives: Preferences and Value Tradeoffs. Wiley & Sons 1976. This is an older work, but very good. It's mathematically more rigorous and important if you want to understand additive and multiplicative models.
Both of them are practical and give good examples. The first one is easier to read. If you're not afraid of more complicated mathematics, I can also give you some more other references. I guess you wouldn't be asking me then, however, because there is plenty of sources. I generally recommend Peter C. Fishburn's work, insofar as I can understand it -- some of it is too hard for me.