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The multiplicative weight updates method for evolutionary biology

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TitleInfo
Title
The multiplicative weight updates method for evolutionary biology
Name (type = personal)
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Chastain
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Erick
NamePart (type = date)
1984-
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Erick Chastain
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author
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Eric
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Eric Allender
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Advisory Committee
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chair
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Fefferman
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Nina
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Nina Fefferman
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Wright
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Rebecca
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Rebecca Wright
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Advisory Committee
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internal member
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Saraf
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Shubhangi
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Shubhangi Saraf
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Advisory Committee
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Mehta
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Ruhta
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Ruhta Mehta
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Advisory Committee
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outside member
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Rutgers University
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degree grantor
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Graduate School - New Brunswick
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school
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theses
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DateCreated (qualifier = exact)
2017
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2017-01
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2017
Place
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xx
Language
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eng
Abstract (type = abstract)
A new and exciting direction of recent work in theoretical computer science is the application of methods from the field to evolutionary biology. Starting with the work of Christos Papadimitriou and Adi Livnat, there has been a concerted effort to use these techniques to analyze such diverse phenomena as: the algorithmic role of recombination to increase mixability, the evolution of modularity, and the evolution of complex adaptations. There is also work by Les Valiant and his students using tools primarily from learning theory to more broadly analyze evolutionary processes. In parallel, computer science theory has developed a novel method which has been applied in diverse areas of algorithms and complexity: the Multiplicative Weight Updates (MWU) method. The MWU method simply applies the MWU general-purpose online learning algorithm on problem-specific loss functions. The contribution of this thesis is to apply the MWU method and the algorithmic lens to make models in evolutionary biology. The first contribution is a surprising equivalence between the MWU algorithm playing a coordination game and infinite-population genetics models with recombination and no mutation. By so doing, we resolve analytically a question asked by Papadimitriou and Livnat: whether mixability is increased in the short-term by recombination. Other models introduced using MWU as a basic dynamics include a model of the evolution of animal personality and of tool innovation. Finally, the thesis presents a novel connection between universal semantic communication and the Rivoire-Leibler model of population genetics, in addition to infinite population asexual selection models. MWU is the basic tool used to prove the latter connection.
Subject (authority = RUETD)
Topic
Computer Science
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Title
Rutgers University Electronic Theses and Dissertations
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ETD
Identifier
ETD_7860
PhysicalDescription
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electronic resource
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application/pdf
InternetMediaType
text/xml
Extent
1 online resource (viii, 146 p.)
Note (type = degree)
Ph.D.
Note (type = bibliography)
Includes bibliographical references
Subject (authority = ETD-LCSH)
Topic
Evolution (Biology)
Note (type = statement of responsibility)
by Erick Chastain
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TitleInfo
Title
Graduate School - New Brunswick Electronic Theses and Dissertations
Identifier (type = local)
rucore19991600001
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NjNbRU
Identifier (type = doi)
doi:10.7282/T3N300CZ
Genre (authority = ExL-Esploro)
ETD doctoral
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Rights

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The author owns the copyright to this work.
RightsHolder (type = personal)
Name
FamilyName
Chastain
GivenName
Erick
Role
Copyright Holder
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Type
Permission or license
DateTime (encoding = w3cdtf); (qualifier = exact); (point = start)
2017-01-12 15:51:53
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Name
Erick Chastain
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Affiliation
Rutgers University. Graduate School - New Brunswick
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License
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Author Agreement License
Detail
I hereby grant to the Rutgers University Libraries and to my school the non-exclusive right to archive, reproduce and distribute my thesis or dissertation, in whole or in part, and/or my abstract, in whole or in part, in and from an electronic format, subject to the release date subsequently stipulated in this submittal form and approved by my school. I represent and stipulate that the thesis or dissertation and its abstract are my original work, that they do not infringe or violate any rights of others, and that I make these grants as the sole owner of the rights to my thesis or dissertation and its abstract. I represent that I have obtained written permissions, when necessary, from the owner(s) of each third party copyrighted matter to be included in my thesis or dissertation and will supply copies of such upon request by my school. I acknowledge that RU ETD and my school will not distribute my thesis or dissertation or its abstract if, in their reasonable judgment, they believe all such rights have not been secured. I acknowledge that I retain ownership rights to the copyright of my work. I also retain the right to use all or part of this thesis or dissertation in future works, such as articles or books.
Copyright
Status
Copyright protected
Availability
Status
Open
Reason
Permission or license
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2017-01-12T20:39:41
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