PhilSci Archive

Local, General and Universal Prediction Strategies: A Game-Theoretical Approach to the Problem of Induction

Schurz, Gerhard (2008) Local, General and Universal Prediction Strategies: A Game-Theoretical Approach to the Problem of Induction. In: UNSPECIFIED.

This is the latest version of this item.

[img]
Preview
 PDF
EPSA07SchurzPaper.pdf
Download (308kB)

Abstract

In this paper I present a game-theoretical approach to the problem of induction. I investigate the comparative success of prediction methods by mathematical analysis and computer programming. Hume's problem lies in the fact that although the success of object-inductive prediction strategies is quite robust, they cannot be universally optimal. My proposal towards a solution of the problem of induction is meta-induction. I show that there exist meta-inductive prediction strategies whose success is universally optimal, modulo short-run losses which are upper-bounded. I then turn to the implications of my approach for the evolution of cognition. In the final section I suggest a revision of the paradigm of bounded rationality by introducing the distinction between local, general and universal prediction strategies.

Export/Citation: EndNote | BibTeX | Dublin Core | ASCII/Text Citation (Chicago) | HTML Citation | OpenURL
Social Networking:
Share |
Item Type: Conference or Workshop Item (UNSPECIFIED)
Creators:
CreatorsEmailORCID
Schurz, Gerhard
Keywords: Problem of Induction, Meta-Induction, Prediction Method, Optimality, Universality, Bounded Rationality, Take the Best, Evolution of Cognition
Subjects: General Issues > Confirmation/Induction
Depositing User: Gerhard Schurz
Date Deposited: 14 Mar 2008
Last Modified: 07 Oct 2010 15:16
Item ID: 3944
Subjects: General Issues > Confirmation/Induction
Date: 2008
URI: https://philsci-archive.pitt.edu/id/eprint/3944

Available Versions of this Item

Monthly Views for the past 3 years

Monthly Downloads for the past 3 years

Plum Analytics

Actions (login required)

View Item View Item