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" ADAPTIVE LEARNING AMONG INTERACTING AGENTS: AN ANALYSIS OF THE MANY-AGENT, LONG-TERM LIMIT "


Document Type : Latin Dissertation
Language of Document : English
Record Number : 150763
Doc. No : ET22555
Main Entry : JOHN P. CURRAN
Title Proper : ADAPTIVE LEARNING AMONG INTERACTING AGENTS: AN ANALYSIS OF THE MANY-AGENT, LONG-TERM LIMIT
Note : This document is digital این مدرک بصورت الکترونیکی می باشد
Abstract : A variety of systems in the social sciences and engineering can be modeled, with greater orlesser fidelity, as decentralized dynamical systems consisting of a loose collection of agentsusing adaptive algorithms, and influencing each other indirectly through the cumulativeeffect of their decisions. Models of this type suggest how the systems might evolve,and what parameters are essential in modeling the system. The emphasis is on studyingrelatively simple models, which are intended to capture at least some of the importantfeatures of the system.One example of this kind of model is a dynamical model for discrete choice among....-...,..tested for theQ1 PC1 bus cardBoth these projects mere sofixare des elopment efforts tonards contributing to dlfferentaspects of Roboucs and lZ1echatronics projects m the Controls and Roboucs Group..
Subject : Electericl tess
: برق
electronic file name : TL45778.pdf
Title and statement of responsibility and : ADAPTIVE LEARNING AMONG INTERACTING AGENTS: AN ANALYSIS OF THE MANY-AGENT, LONG-TERM LIMIT [Thesis]
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TL45778.pdf
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