Wissen gewinnen und gewinnen durch Wissen
[Gaining knowledge and winning with knowledge]
AbstractAccording to Alfred Korzybski (1921) humans unlike plants and animals have the property to bind time, i.e. they are able to transfer experience through time. Humans are capable to collenct knowledge from the past and communicate their knowledge to the future. This paper investigates the possibilities and limitations to describe this capability by algorithms and implement it in artificial learning systems.
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Bibliographic InfoPaper provided by University Library of Munich, Germany in its series MPRA Paper with number 2838.
Date of creation: Aug 2000
Date of revision:
knowledge; game theory; artificial adaptive agents; learning classifier systems; genetic algorithms;
Find related papers by JEL classification:
- C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
- C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
- C72 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Noncooperative Games
- C73 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Stochastic and Dynamic Games; Evolutionary Games
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Martin J Osborne & Ariel Rubinstein, 2009.
"A Course in Game Theory,"
814577000000000225, UCLA Department of Economics.
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