Kenny Easwaran
Dados Biográficos
| ID | 919014 |
|---|---|
| NOME | Kenny Easwaran |
| PRENOMES | Kenny |
| SOBRENOME | Easwaran |
| ASSINATURA | EASWARAN K |
| AFILIAÇÕES | University of Southern California |
| ORCID | 0000-0002-2278-6257 |
| VERIFICADO | Sim |
| TOTAL DE OBRAS | 13 |
| TOTAL DE CITAÇÕES | 183 |
| TOTAL COMO AUTOR | 13 |
| TOTAL COMO EDITOR | 0 |
| PRIMEIRO ANO DE PUBLICAÇÃO | 2008 |
| ANO MAIS RECENTE DE PUBLICAÇÃO | 2026 |
| ÍNDICE H | 5 |
Generalizations of risk-weighted expected utility
Buchak’s risk-weighted expected utility considers not just the probability of an outcome, but also the probability of getting a strictly better outcome, when weighting the contribution that outcome gives to the evaluation of a gamble. It uses a risk-weighting function $R$ sending probabilities in $\left[ {0,1} \right]$ to decision weights $\left[ {0,1} \right]$ . I adapt this to allow weights in any real interval. Finite intervals yield nothing n…
Tickles, iteration, and habits
At first pass, Evidential Decision Theory (EDT) recommends one-boxing in Newcomb’s Problem and Causal Decision Theory (CDT) recommends two-boxing. However, it has been acknowledged that concrete instances of the problem have messy features complicating their analyses. Recently, a third competitor, Functional Decision Theory (FDT) has emerged recommending one-boxing in some versions and two-boxing in others. This paper explores the verdicts of the…
A classification of Newcomb problems and decision theories
Redefine statistical significance
Quitting Certainties
Rebutting and Undercutting in Mathematics
In my ( ) I argued that a central component of mathematical practice is that published proofs must be “transferable” — that is, they must be such that the author's reasons for believing the conclusion are shared directly with the reader, rather than requiring the reader to essentially rely on testimony. The goal of this paper is to explain this requirement of transferability in terms of a more general norm on defeat in mathematical reasoning that…
Regularity and Hyperreal Credences
Many philosophers have become worried about the use of standard real numbers for the probability function that represents an agent's credences. They point out that real numbers can't capture the distinction between certain extremely unlikely events and genuinely impossible ones—they are both represented by credence 0, which violates a principle known as “regularity.” Following Skyrms 1980 and Lewis 1980, they recommend that we should instead use …
Why Physics Uses Second Derivatives
I defend a causal reductionist account of the nature of rates of change like velocity and acceleration. This account identifies velocity with the past derivative of position and acceleration with the future derivative of velocity. Unlike most reductionist accounts, it can preserve the role of velocity as a cause of future positions and acceleration as the effect of current forces. I show that this is possible only if all the fundamental laws are …
Probability and Logic
Probability and logic are two branches of mathematics that have important philosophical applications. This article discusses several areas of intersection between them. Several involve the role for probability in giving semantics for logic or the role of logic in governing assignments of probability. Some involve probability over non-classical logic or self-referential sentences
Expected Accuracy Supports Conditionalization—and Conglomerability and Reflection
Expected accuracy arguments have been used by several authors (Leitgeb and Pettigrew and Greaves and Wallace) to support the diachronic principle of conditionalization, in updates where there are only finitely many possible propositions to learn. I show that these arguments can be extended to infinite cases, giving an argument not just for conditionalization but also for principles known as ‘conglomerability’ and ‘reflection’. This shows that the…
Bayesianism I
Bayesianism is a popular position (or perhaps, positions) in the philosophy of science, epistemology, statistics, and other related areas, which represents belief as coming in degrees, measured by a probability function. In this article, I give an overview of the unifying features of the different positions called 'Bayesianism', and discuss several of the arguments traditionally used to support them
Bayesianism II
In the first paper, I discussed the basic claims of Bayesianism (that degrees of belief are important, that they obey the axioms of probability theory, and that they are rationally updated by either standard or Jeffrey conditionalization) and the arguments that are often used to support them. In this paper, I will discuss some applications these ideas have had in confirmation theory, epistemology, and statistics, and criticisms of these applicati…
Tracking Reason
Book Review| April 01 2008 Tracking Reason: Proof, Consequence, and Truth Jody Azzouni, Tracking Reason: Proof, Consequence, and Truth. New York: Oxford University Press, 2006. vi + 248 pp. Kenny Easwaran Kenny Easwaran Search for other works by this author on: This Site Google The Philosophical Review (2008) 117 (2): 296–299. https://doi.org/10.1215/00318108-2007-041 Cite Icon Cite Share Icon Share Facebook Twitter LinkedIn MailTo Permissions Se…
Redefine statistical significance
Regularity and Hyperreal Credences
Many philosophers have become worried about the use of standard real numbers for the probability function that represents an agent's credences. They point out that real numbers can't capture the distinction between certain extremely unlikely events and genuinely impossible ones—they are both represented by credence 0, which violates a principle known as “regularity.” Following Skyrms 1980 and Lewis 1980, they recommend that we should instead use …
Bayesianism I
Bayesianism is a popular position (or perhaps, positions) in the philosophy of science, epistemology, statistics, and other related areas, which represents belief as coming in degrees, measured by a probability function. In this article, I give an overview of the unifying features of the different positions called 'Bayesianism', and discuss several of the arguments traditionally used to support them
Expected Accuracy Supports Conditionalization—and Conglomerability and Reflection
Expected accuracy arguments have been used by several authors (Leitgeb and Pettigrew and Greaves and Wallace) to support the diachronic principle of conditionalization, in updates where there are only finitely many possible propositions to learn. I show that these arguments can be extended to infinite cases, giving an argument not just for conditionalization but also for principles known as ‘conglomerability’ and ‘reflection’. This shows that the…
Bayesianism II
In the first paper, I discussed the basic claims of Bayesianism (that degrees of belief are important, that they obey the axioms of probability theory, and that they are rationally updated by either standard or Jeffrey conditionalization) and the arguments that are often used to support them. In this paper, I will discuss some applications these ideas have had in confirmation theory, epistemology, and statistics, and criticisms of these applicati…
Why Physics Uses Second Derivatives
I defend a causal reductionist account of the nature of rates of change like velocity and acceleration. This account identifies velocity with the past derivative of position and acceleration with the future derivative of velocity. Unlike most reductionist accounts, it can preserve the role of velocity as a cause of future positions and acceleration as the effect of current forces. I show that this is possible only if all the fundamental laws are …
Rebutting and Undercutting in Mathematics
In my ( ) I argued that a central component of mathematical practice is that published proofs must be “transferable” — that is, they must be such that the author's reasons for believing the conclusion are shared directly with the reader, rather than requiring the reader to essentially rely on testimony. The goal of this paper is to explain this requirement of transferability in terms of a more general norm on defeat in mathematical reasoning that…
Tracking Reason
Book Review| April 01 2008 Tracking Reason: Proof, Consequence, and Truth Jody Azzouni, Tracking Reason: Proof, Consequence, and Truth. New York: Oxford University Press, 2006. vi + 248 pp. Kenny Easwaran Kenny Easwaran Search for other works by this author on: This Site Google The Philosophical Review (2008) 117 (2): 296–299. https://doi.org/10.1215/00318108-2007-041 Cite Icon Cite Share Icon Share Facebook Twitter LinkedIn MailTo Permissions Se…
Bayesianism I
Bayesianism is a popular position (or perhaps, positions) in the philosophy of science, epistemology, statistics, and other related areas, which represents belief as coming in degrees, measured by a probability function. In this article, I give an overview of the unifying features of the different positions called 'Bayesianism', and discuss several of the arguments traditionally used to support them
Bayesianism II
In the first paper, I discussed the basic claims of Bayesianism (that degrees of belief are important, that they obey the axioms of probability theory, and that they are rationally updated by either standard or Jeffrey conditionalization) and the arguments that are often used to support them. In this paper, I will discuss some applications these ideas have had in confirmation theory, epistemology, and statistics, and criticisms of these applicati…
Expected Accuracy Supports Conditionalization—and Conglomerability and Reflection
Expected accuracy arguments have been used by several authors (Leitgeb and Pettigrew and Greaves and Wallace) to support the diachronic principle of conditionalization, in updates where there are only finitely many possible propositions to learn. I show that these arguments can be extended to infinite cases, giving an argument not just for conditionalization but also for principles known as ‘conglomerability’ and ‘reflection’. This shows that the…
Regularity and Hyperreal Credences
Many philosophers have become worried about the use of standard real numbers for the probability function that represents an agent's credences. They point out that real numbers can't capture the distinction between certain extremely unlikely events and genuinely impossible ones—they are both represented by credence 0, which violates a principle known as “regularity.” Following Skyrms 1980 and Lewis 1980, they recommend that we should instead use …
Why Physics Uses Second Derivatives
I defend a causal reductionist account of the nature of rates of change like velocity and acceleration. This account identifies velocity with the past derivative of position and acceleration with the future derivative of velocity. Unlike most reductionist accounts, it can preserve the role of velocity as a cause of future positions and acceleration as the effect of current forces. I show that this is possible only if all the fundamental laws are …
Probability and Logic
Probability and logic are two branches of mathematics that have important philosophical applications. This article discusses several areas of intersection between them. Several involve the role for probability in giving semantics for logic or the role of logic in governing assignments of probability. Some involve probability over non-classical logic or self-referential sentences
Rebutting and Undercutting in Mathematics
In my ( ) I argued that a central component of mathematical practice is that published proofs must be “transferable” — that is, they must be such that the author's reasons for believing the conclusion are shared directly with the reader, rather than requiring the reader to essentially rely on testimony. The goal of this paper is to explain this requirement of transferability in terms of a more general norm on defeat in mathematical reasoning that…
Quitting Certainties
Redefine statistical significance
A classification of Newcomb problems and decision theories
Generalizations of risk-weighted expected utility
Buchak’s risk-weighted expected utility considers not just the probability of an outcome, but also the probability of getting a strictly better outcome, when weighting the contribution that outcome gives to the evaluation of a gamble. It uses a risk-weighting function $R$ sending probabilities in $\left[ {0,1} \right]$ to decision weights $\left[ {0,1} \right]$ . I adapt this to allow weights in any real interval. Finite intervals yield nothing n…
Tickles, iteration, and habits
At first pass, Evidential Decision Theory (EDT) recommends one-boxing in Newcomb’s Problem and Causal Decision Theory (CDT) recommends two-boxing. However, it has been acknowledged that concrete instances of the problem have messy features complicating their analyses. Recently, a third competitor, Functional Decision Theory (FDT) has emerged recommending one-boxing in some versions and two-boxing in others. This paper explores the verdicts of the…
Computer Science (9 obras) · Mathematics (9 obras) · Philosophy and History of Science (8 obras) · Epistemology (7 obras) · Philosophy (7 obras) · Epistemology, Ethics, and Metaphysics (5 obras) · Mathematical economics (5 obras) · Philosophy and Theoretical Science (5 obras) · Psychology (4 obras) · Bayesian Modeling and Causal Inference (3 obras)