brook | v1.3.0Aug 11th 2020 | (+66/-11) | ||

Ruby | v1.2.0Apr 11th 2020 | (+143/-24) | ||

Ruby | v1.1.0Apr 11th 2020 | (+253/-2922) | ||

Caspar42 | v0.0.44Oct 6th 2017 | (+80) | ||

Deku-shrub | v0.0.43May 12th 2017 | (+26/-50) /* Commonly discussed decision theories */ | ||

lifelonglearner | v0.0.42May 12th 2017 | /* Commonly discussed decision theories */ | ||

lifelonglearner | v0.0.41May 12th 2017 | (-30) /* Commonly discussed decision theories */ | ||

lifelonglearner | v0.0.40May 12th 2017 | (+80/-1) /* Commonly discussed decision theories */ | ||

lifelonglearner | v0.0.39May 12th 2017 | (+6) /* Commonly discussed decision theories */ | ||

notsonewuser | v0.0.38Apr 5th 2013 | (+43) /* Blog posts */ added Luke's recent "Decision Theory FAQ" |

brookv1.3.0Aug 11th 2020 (+66/-11)

**Decision theory** is the study of principles and algorithms for making correct ~~decisions—~~decisions—that is, decisions that allow an agent to achieve better outcomes with respect to its goals [1].

*See also: Game Theory, Robust Agents, Utility Functions*

The best known decision theories are Causal Decision Theory (CDT) and Evidential Decision Theory (EDT). On LessWrong, an alternative family of decision theories has been discussed heavily with the varying names of Updateless Decision Theory (UDT), Timeless Decision Theory (TDT), and Functional Decision Theory (FDT).~~ ~~

Rubyv1.1.0Apr 11th 2020 (+253/-2922) ~~Thought experiments~~

~~Commonly discussed decision theories~~

~~Blog posts~~

~~Sequence by ~~~~AnnaSalamon~~

~~Sequence by ~~~~orthonormal~~~~ (Decision Theories: A Semi-Formal Analysis)~~

~~See also~~

**Decision theory** is the formal study of ~~principles~~an agent's choices [1].

The best known decision theories are Causal Decision Theory (CDT) and ~~algorithms for making correct decisions—that is, decisions that allow~~Evidential Decision Theory (EDT). On LessWrong, 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.~~

~~The limitations and pathologies~~alternative family of decision theories ~~can be analyzed by considering~~has been discussed heavily with the ~~decisions they suggest in the certain idealized situations that stretch the limits~~varying names 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~~

~~Standard theories well-known in academia:~~

~~Theories invented by researchers associated with ~~~~MIRI~~~~ and LW:~~

~~TDT,~~(UDT), Timeless Decision Theory~~UDT,~~~~Updateless~~(TDT), and Functional Decision Theory~~ADT:~~~~Ambient Decision Theory~~~~(a variant of UDT)~~~~FDT:~~~~Cheating Death in Damascus~~

~~Other decision theories are listed in ~~~~A comprehensive list of decision theories~~ (FDT).

~~Terminal Values and Instrumental Values~~~~Decision Theories: A Less Wrong Primer~~~~by orthonormal~~~~Decision Theory FAQ~~~~by lukeprog and crazy88~~

~~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~~

~~Part 0: Decision Theories: A Less Wrong Primer~~~~Part I: The Problem with Naive Decision Theory~~~~Part II: Causal Decision Theory and Substitution~~~~Part III: Formalizing Timeless Decision Theory~~

Caspar42v0.0.44Oct 6th 2017 (+80) ## Thought experiments

## Commonly discussed decision theories

## Blog posts

## Sequence by AnnaSalamon

## Sequence by orthonormal (Decision Theories: A Semi-Formal Analysis)

## See also

**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.

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

Standard theories well-known in academia:

Theories invented by researchers associated with MIRI and LW:

- TDT, Timeless Decision Theory
- UDT, Updateless Decision Theory
- ADT: Ambient Decision Theory (a variant of UDT)
- FDT: Cheating Death in Damascus

Other decision theories are listed in A comprehensive list of decision theories.

- Terminal Values and Instrumental Values
- Decision Theories: A Less Wrong Primer by orthonormal
- Decision Theory FAQ by lukeprog and crazy88

- 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

- Part 0: Decision Theories: A Less Wrong Primer
- Part I: The Problem with Naive Decision Theory
- Part II: Causal Decision Theory and Substitution
- Part III: Formalizing Timeless Decision Theory

- Instrumental rationality
- Causality
- Expected utility
- Evidential Decision Theory
- Timeless decision theory, Updateless decision theory
- AIXI

Deku-shrubv0.0.43May 12th 2017 (+26/-50) /* Commonly discussed decision theories */## Thought experiments

## Commonly discussed decision theories

## Blog posts

## Sequence by AnnaSalamon

## Sequence by orthonormal (Decision Theories: A Semi-Formal Analysis)

## See also

**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.

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

Standard theories well-known in academia:

Theories invented by researchers associated with MIRI and LW:

- TDT, Timeless Decision Theory
- UDT, Updateless Decision Theory
- ADT: Ambient Decision Theory (a variant of UDT)
- FDT:
~~https://intelligence.org/files/DeathInDamascus.pdf~~Cheating Death in Damascus

- Terminal Values and Instrumental Values
- Decision Theories: A Less Wrong Primer by orthonormal
- Decision Theory FAQ by lukeprog and crazy88

- 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

- Part 0: Decision Theories: A Less Wrong Primer
- Part I: The Problem with Naive Decision Theory
- Part II: Causal Decision Theory and Substitution
- Part III: Formalizing Timeless Decision Theory

- Instrumental rationality
- Causality
- Expected utility
- Evidential Decision Theory
- Timeless decision theory, Updateless decision theory
- AIXI

lifelonglearnerv0.0.41May 12th 2017 (-30) /* Commonly discussed decision theories */## Thought experiments

## Commonly discussed decision theories

## Blog posts

## Sequence by AnnaSalamon

## Sequence by orthonormal (Decision Theories: A Semi-Formal Analysis)

## See also

**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.

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

Standard theories well-known in academia:

Theories invented by researchers associated with MIRI and LW:

- TDT, Timeless Decision Theory
- UDT, Updateless Decision Theory
- ADT: Ambient Decision Theory (a variant of UDT)
- FDT:
~~[[Functional Decision Theory]~~https://intelligence.org/files/DeathInDamascus.pdf~~]~~

- Terminal Values and Instrumental Values
- Decision Theories: A Less Wrong Primer by orthonormal
- Decision Theory FAQ by lukeprog and crazy88

- 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

- Part 0: Decision Theories: A Less Wrong Primer
- Part I: The Problem with Naive Decision Theory
- Part II: Causal Decision Theory and Substitution
- Part III: Formalizing Timeless Decision Theory

- Instrumental rationality
- Causality
- Expected utility
- Evidential Decision Theory
- Timeless decision theory, Updateless decision theory
- AIXI

lifelonglearnerv0.0.40May 12th 2017 (+80/-1) /* Commonly discussed decision theories */## 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:

## Commonly discussed decision theories

## Blog posts

## Sequence by AnnaSalamon

## Sequence by orthonormal (Decision Theories: A Semi-Formal Analysis)

## See also

**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.

*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.

- Newcomb's problem
- Counterfactual mugging
- Parfit's hitchhiker
- Smoker's lesion
- Absentminded driver
- Sleeping Beauty problem
- Prisoner's dilemma
- Pascal's mugging

Standard theories well-known in academia:

Theories invented by researchers associated with MIRI and LW:

- TDT, Timeless Decision Theory
- UDT, Updateless Decision Theory
- ADT: Ambient Decision Theory (a variant of UDT)
- FDT: [[Functional Decision Theory]
~~1~~https://intelligence.org/files/DeathInDamascus.pdf]

- Terminal Values and Instrumental Values
- Decision Theories: A Less Wrong Primer by orthonormal
- Decision Theory FAQ by lukeprog and crazy88

- 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

- Part 0: Decision Theories: A Less Wrong Primer
- Part I: The Problem with Naive Decision Theory
- Part II: Causal Decision Theory and Substitution
- Part III: Formalizing Timeless Decision Theory

- Instrumental rationality
- Causality
- Expected utility
- Evidential Decision Theory
- Timeless decision theory, Updateless decision theory
- AIXI

lifelonglearnerv0.0.39May 12th 2017 (+6) /* Commonly discussed decision theories */## 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:

## Commonly discussed decision theories

## Blog posts

## Sequence by AnnaSalamon

## Sequence by orthonormal (Decision Theories: A Semi-Formal Analysis)

## See also

**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.

*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.

- Newcomb's problem
- Counterfactual mugging
- Parfit's hitchhiker
- Smoker's lesion
- Absentminded driver
- Sleeping Beauty problem
- Prisoner's dilemma
- Pascal's mugging

Standard theories well-known in academia:

Theories invented by researchers associated with MIRI and LW:

- TDT, Timeless Decision Theory
- UDT, Updateless Decision Theory
- ADT: Ambient Decision Theory (a variant of UDT)
- FDT: 1

- Terminal Values and Instrumental Values
- Decision Theories: A Less Wrong Primer by orthonormal
- Decision Theory FAQ by lukeprog and crazy88

- 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

- Part 0: Decision Theories: A Less Wrong Primer
- Part I: The Problem with Naive Decision Theory
- Part II: Causal Decision Theory and Substitution
- Part III: Formalizing Timeless Decision Theory

- Instrumental rationality
- Causality
- Expected utility
- Evidential Decision Theory
- Timeless decision theory, Updateless decision theory
- AIXI

notsonewuserv0.0.38Apr 5th 2013 (+43) /* Blog posts */ added Luke's recent "Decision Theory FAQ"## 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:

## Commonly discussed decision theories

## Blog posts

## Sequence by AnnaSalamon

## Sequence by orthonormal (Decision Theories: A Semi-Formal Analysis)

## See also

Load More (10/48)**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.

*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.

- Newcomb's problem
- Counterfactual mugging
- Parfit's hitchhiker
- Smoker's lesion
- Absentminded driver
- Sleeping Beauty problem
- Prisoner's dilemma
- Pascal's mugging

Standard theories well-known in academia:

Theories invented by researchers associated with MIRI and LW:

- TDT, Timeless Decision Theory
- UDT, Updateless Decision Theory
- ADT: Ambient Decision Theory (a variant of UDT)

- Terminal Values and Instrumental Values
- Decision Theories: A Less Wrong Primer by orthonormal
- Decision Theory FAQ by lukeprog and crazy88

- 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

- Part 0: Decision Theories: A Less Wrong Primer
- Part I: The Problem with Naive Decision Theory
- Part II: Causal Decision Theory and Substitution
- Part III: Formalizing Timeless Decision Theory