Difference between revisions of "Decision theory"
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*[http://lesswrong.com/lw/17b/decision_theory_why_pearl_helps_reduce_could_and/ Why Pearl helps reduce “could” and “would”, but still leaves us with at least three alternatives] | *[http://lesswrong.com/lw/17b/decision_theory_why_pearl_helps_reduce_could_and/ Why Pearl helps reduce “could” and “would”, but still leaves us with at least three alternatives] | ||
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* CDT: [http://en.wikipedia.org/wiki/Causal_decision_theory Causal Decision Theory] | * CDT: [http://en.wikipedia.org/wiki/Causal_decision_theory Causal Decision Theory] | ||
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| + | * ADT: [[Ambient decision theory|Ambient Decision Theory]] | ||
* XDT: [http://lesswrong.com/lw/15m/towards_a_new_decision_theory/11jo?c=1 Exceptionless Decision Theory] | * XDT: [http://lesswrong.com/lw/15m/towards_a_new_decision_theory/11jo?c=1 Exceptionless Decision Theory] | ||
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==See also== | ==See also== | ||
Revision as of 22:44, 9 October 2010
Decision theory is the study of principles and algorithms for making correct decisions—that is, decisions that allow an agent to achieve better outcomes with respect to its goals. Every action at least implicitly represents a decision under uncertainty: in a state of partial knowledge, something has to be done, even if that something turns out to be nothing (call it "the null action"). Even if you don't know how you make decisions, decisions do get made, and so there has to be some underlying mechanism. What is it? And how can it be done better? Decision theory has the answers.
A core idea in decision theory is that of expected utility maximization, usually intractable to directly calculate in practice, but an invaluable theoretical concept. An agent assigns utility to every possible outcome: a real number representing the goodness or desirability of that outcome. The mapping of outcomes to utilities is called the agent's utility function. (The utility function is said to be invariant under affine transformations: that is, the utilities can be scaled or translated by a constant while resulting in all the same decisions.) For every action that the agent could take, sum over the utilities of the various possible outcomes weighted by their probability: this is the expected utility of the action, and the action with the highest expected utility is to be chosen.
Thought experiments
The limitations and pathologies of decision theories can be analyzed by considering the decisions they suggest in the certain idealized situations that stretch the limits of decision theory's applicability. Some of the thought experiments more frequently discussed on LW include:
- Newcomb's problem
- Counterfactual mugging
- Parfit's hitchhiker
- Smoker's lesion
- Absentminded driver
- Sleeping Beauty problem
- Prisoner's dilemma
- Pascal's mugging
Blog posts
Sequence
- Decision theory: An outline of some upcoming posts
- Confusion about Newcomb is confusion about counterfactuals
- Why we need to reduce “could”, “would”, “should”
- Why Pearl helps reduce “could” and “would”, but still leaves us with at least three alternatives
Common abbreviations
- CDT: Causal Decision Theory
- EDT: Evidential Decision Theory
- TDT: Timeless Decision Theory (LW-only)
- UDT: Updateless Decision Theory (LW-only)
More rarely used:
See also
- Instrumental rationality
- Causality
- Expected utility
- Timeless decision theory, Updateless decision theory
