During his time as a research fellow for MIRI, Alex Altair wrote a paper on Timeless Decision Theory (TDT) that has now been published: “A Comparison of Decision Algorithms on Newcomblike Problems.”
Altair’s paper is both more succinct and also more precise in its formulation of TDT than Yudkowsky’s earlier paper “Timeless Decision Theory.” Thus, Altair’s paper should serve as a handy introduction to TDT for philosophers, computer scientists, and mathematicians, while Yudkowsky’s paper remains required reading for anyone interested to develop TDT further, for it covers more ground than Altair’s paper.
Altair’s abstract reads:
When formulated using Bayesian networks, two standard decision algorithms (Evidential Decision Theory and Causal Decision Theory) can be shown to fail systematically when faced with aspects of the prisoner’s dilemma and so-called “Newcomblike” problems. We describe a new form of decision algorithm, called Timeless Decision Theory, which consistently wins on these problems.
We may submit to a journal later, but we’ve published the current version to our website so that readers won’t need to wait two years (from submission to acceptance to publication) to read it.
For a gentle introduction to the entire field of normative decision theory (including TDT), see Muehlhauser and Williamson’s Decision Theory FAQ.
