Reflective Oracles: A Foundation for Classical Game Theory
@article{Fallenstein2015ReflectiveOA, title={Reflective Oracles: A Foundation for Classical Game Theory}, author={Benja Fallenstein and Jessica Taylor and Paul Francis Christiano}, journal={ArXiv}, year={2015}, volume={abs/1508.04145} }
Classical game theory treats players as special---a description of a game contains a full, explicit enumeration of all players---even though in the real world, "players" are no more fundamentally special than rocks or clouds. It isn't trivial to find a decision-theoretic foundation for game theory in which an agent's coplayers are a non-distinguished part of the agent's environment. Attempts to model both players and the environment as Turing machines, for example, fail for standard…
5 Citations
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References
SHOWING 1-10 OF 29 REFERENCES
Reflective Oracles: A Foundation for Game Theory in Artificial Intelligence
- Computer ScienceLORI
- 2015
This paper proposes a framework in which agents and their environments are both modelled as probablistic oracle machines with access to a “reflective” oracle, which is able to answer questions about the outputs of other machines with Access to the same oracle.
Modeling Rational Players: Part I
- EconomicsEconomics and Philosophy
- 1987
Game theory has proved a useful tool in the study of simple economic models. However, numerous foundational issues remain unresolved. The situation is particularly confusing in respect of the…
BOUNDED RATIONALITY
- Psychology, Economics
- 1999
Findings from behavioral organization theory, behavioral decision theory, survey research, and experimental economics leave no doubt about the failure of rational choice as a descriptive model of…
Theory of Recursive Functions and Effective Computability
- Computer Science
- 1969
If searching for the ebook by Hartley Rogers Theory of Recursive Functions and Effective Computability in pdf format, then you've come to the faithful site. We presented the complete version of this…
Game theory.
- PsychologyWiley interdisciplinary reviews. Cognitive science
- 2011
The nature of game-theoretic analysis, the history of game theory,Why game theory is useful for understanding human psychology, and why game theory has played a key role in the recent explosion of interest in the field of behavioral economics are discussed.
Space-Time Embedded Intelligence
- Computer ScienceAGI
- 2012
This paper presents the first formal measure of intelligence for agents fully embedded within their environment that merges and goes beyond Legg's and Russell's, leading to a new, more realistic definition of artificial intelligence that is called Space-Time Embedded Intelligence.
Letter to the Editor: Research Priorities for Robust and Beneficial Artificial Intelligence: An Open Letter
- Computer ScienceAI Mag.
- 2015
It is believed that research on how to make AI systems robust and beneficial is both important and timely, and that there are concrete research directions that can be pursued today.
Universal Artificial Intellegence - Sequential Decisions Based on Algorithmic Probability
- EducationTexts in Theoretical Computer Science. An EATCS Series
- 2005
Reading a book as this universal artificial intelligence sequential decisions based on algorithmic probability and other references can enrich your life quality.