Local Interactions, Learning and Automata Networks in Games

This dissertation is an attempt of expanding the domain of game theory into the sphere of evolving, potentially non-equilibrium systems. We especially focus our attention on studying the effects of local interactions, using automata networks as a modelling tool. The Chapters 2 and 3 of this dissertation concentrate on applications of the local nature of interactions and rely on automata networks as an investigating and modelling tool for game theory. Chapter 2 is devoted to cooperation and to a smaller extent to the endogenous formation of links between the agents. Chapter 3 is investigating the deterministic and stochastic best response play when interactions are local.

Name thesis:degree_name

Ph. D.

Level thesis:degree_level

doctoral

Discipline thesis:degree_discipline

Economics

Department dc:contributor.department

Economics (Arts and Sciences)

Grantor dc:publisher

Virginia Tech

Year dc:date.issued

1998

Author dc:creator

• Outkin, Alexander V.

Chairs dc:contributor.committeechair

• Haller, Hans H.
• Stegeman, Mark

Committee members dc:contributor.committeemember

• Snyder, Susan K.
• Gilles, Robert P.
• Kats, Amoz

• automata networks
• learning
• evolution
• cooperation

Statement dc:rights

• In Copyright

Licence dc:rights.uri

• http://rightsstatements.org/vocab/InC/1.0/

Language dc:language.iso

en

Dc Identifier Other

etd-110498-170256

OAI identifier oai:identifier

oai:vtechworks.lib.vt.edu:10919/29465