Updateless Decision Theory

A robust theory of logical uncertainty is essential to a full formalization of UDT.  A UDT agent must calculate probabilities and expected values on the outcome of its possible actions in all possible worlds--sequences of observations and its own actions. However, it does not know its own actions in all possible worlds. (The whole point is to derive its actions.) On the other hand, it does have some knowledge about its actions, just as you know that you are unlikely to walk straight into a wall the next chance you get. So, the UDT agent models itself as an algorithm, and its probability distribution about what it itself will do is an important input into its maximization calculation.

One valuable insight from EDT is reflected in "UDT 1.1" (see article by McAllister in references), a variant of UDT in which the agent takes into account that some of its algorithm (mapping from observations to actions) may be prespecified and not entirely in its control, so that it has to gather evidence and draw conclusions about part of its own mental makeup. The difference between UDT 1.0 and 1.1 is that UDT 1.1 iterates over policies, whereas UDT 1.0 iterates over actions. 

UDT is very similar to Functional Decision Theory (FDT), but there are differences. FDT doesn't include the UDT1.1 fix and Nate SoarsSoares states: "Wei Dai doesn't endorse FDT's focus on causal-graph-style counterpossible reasoning; IIRC he's holding out for an approach to counterpossible reasoning that falls out of evidential-style conditioning on a logically uncertain distribution". Rob BesingerBensinger says that he's heard UDT described as "FDT + a theory of anthropics".

UDT is very similar to Functional Decision Theory (FDT), but there are difference.differences. FDT doesn't include the UDT1.1 fix and Nate Soars states: "Wei Dai doesn't endorse FDT's focus on causal-graph-style counterpossible reasoning; IIRC he's holding out for an approach to counterpossible reasoning that falls out of evidential-style conditioning on a logically uncertain distribution". Rob Besinger says that he's heard UDT described as "FDT + a theory of anthropics".

Applied to The Absent-Minded Driver by ESRogs at 9mo
Applied to Updatelessness and Son of X by ESRogs at 9mo
Applied to UDT as a Nash Equilibrium by ESRogs at 9mo

Updateless Decision Theory (UDT) is a new decision theory meant to deal with a fundamental problem in the existing decision theories: the need to treat the agent as a part of the world in which it makes its decisions. In contrast, in the most common decision theory today, Causal Decision Theory (CDT), the deciding agent is not part of the world model--its decision is the output of the CDT, but the agent's decision in the world context is "magic": in the moment of deciding, no causal links feed into its chosen action. It acts as though its decision was causeless, as in some dualist free-will theories.