Philosophy Dictionary of ArgumentsHome
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| Decision theory: Decision theory is the study of how to make optimal decisions in the face of uncertainty. It is a branch of applied probability theory and analytic philosophy.
Decision theory uses mathematical models to represent decision problems and to identify the best decision to make in a given situation. These models take into account the different options that are available, the probabilities of different outcomes, and the value of different outcomes.
_____________Annotation: The above characterizations of concepts are neither definitions nor exhausting presentations of problems related to them. Instead, they are intended to give a short introduction to the contributions below. – Lexicon of Arguments. | |||
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Tom Griffiths on Decision Theory - Dictionary of Arguments
Brockman I 131 Decision Theory/artificial intelligence/Griffiths: (…) heuristic is a reasonable strategy for avoiding complex probabilistic computations, but also results in errors. For instance, relying on the ease of generating an event from memory as a guide to its probability leads us to overestimate the chances of extreme (hence extremely memorable) events such as terrorist attacks. Heuristics provide a more accurate model of human cognition but one that is not easily generalizable. How do we know which heuristic people might use in a particular situation? Are there other heuristics they use that we just haven’t discovered yet? A problem with using rationality as a basis for describing the behavior of any real-world agent is that, in many situations, calculating the rational action requires the agent to possess a huge amount of computational resources. Cost of computation: Real agents need to modulate the amount of time they spend thinking by the effect the extra thought has on the results of a decision. Solution: Bounded optimality: You trade off the time you spend looking with the difference it makes in the quality of the outcome. This trade-off can be formalized, resulting in a model of rational behavior that artificial-intelligence researchers call “bounded optimality.” The bounded-optimal agent doesn’t focus on always choosing exactly the right action to take but rather on finding the right algorithm to follow in order to find the perfect balance between making mistakes and thinking too much. >Bounded optimality/Griffiths. Griffiths, Tom, “The Artificial Use of Human Beings” in: Brockman, John (ed.) 2019. Twenty-Five Ways of Looking at AI. New York: Penguin Press._____________Explanation of symbols: Roman numerals indicate the source, arabic numerals indicate the page number. The corresponding books are indicated on the right hand side. ((s)…): Comment by the sender of the contribution. Translations: Dictionary of Arguments The note [Concept/Author], [Author1]Vs[Author2] or [Author]Vs[term] resp. "problem:"/"solution:", "old:"/"new:" and "thesis:" is an addition from the Dictionary of Arguments. If a German edition is specified, the page numbers refer to this edition. |
Griffiths, Tom Brockman I John Brockman Possible Minds: Twenty-Five Ways of Looking at AI New York 2019 |
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> Counter arguments against Griffiths
> Counter arguments in relation to Decision Theory
Ed. Martin Schulz, access date 2024-04-28