21,941 research outputs found
Combinatorial structures to construct simple games and molecules
We connect three different topics: combinatorial structures, game theory and chemistry. In particular, we establish the bases to represent some simple games, defined as influence games, and molecules, defined from atoms, by using combinatorial structures. First, we characterize simple games as influence games using influence graphs. It let us to modeling simple games as combinatorial structures (from the viewpoint of structures or graphs). Second, we formally define molecules as combinations of atoms. It let us to modeling molecules as combinatorial structures (from the viewpoint of combinations). It is open to generate such combinatorial structures using some specific techniques as genetic algorithms, (meta-) heuristics algorithms and parallel programming, among others.Peer ReviewedPostprint (published version
Automata-based adaptive behavior for economic modeling using game theory
In this paper, we deal with some specific domains of applications to game
theory. This is one of the major class of models in the new approaches of
modelling in the economic domain. For that, we use genetic automata which allow
to buid adaptive strategies for the players. We explain how the automata-based
formalism proposed - matrix representation of automata with multiplicities -
allows to define a semi-distance between the strategy behaviors. With that
tools, we are able to generate an automatic processus to compute emergent
systems of entities whose behaviors are represented by these genetic automata
Beyond foraging: behavioral science and the future of institutional economics
Institutions affect economic outcomes, but variation in them cannot be directly linked to environmental factors such as geography, climate, or technological availabilities. Game theoretic approaches, based as they typically are on foraging only assumptions, do not provide an adequate foundation for understanding the intervening role of politics and ideology; nor does the view that culture and institutions are entirely socially constructed. Understanding what institutions are and how they influence behavior requires an approach that is in part biological, focusing on cognitive and behavioral adaptations for social interaction favored in the past by group selection. These adaptations, along with their effects on canalizing social learning, help to explain uniformities in political and social order, and are the bedrock upon which we build cultural and institutional variability
Automata-based Adaptive Behavior for Economical Modelling Using Game Theory
In this chapter, we deal with some specific domains of applications to game
theory. This is one of the major class of models in the new approaches of
modelling in the economic domain. For that, we use genetic automata which allow
to build adaptive strategies for the players. We explain how the automata-based
formalism proposed - matrix representation of automata with multiplicities -
allows to define semi-distance between the strategy behaviors. With that tools,
we are able to generate an automatic processus to compute emergent systems of
entities whose behaviors are represented by these genetic automata
Three Essays on Game Theory and Computation
The results section of my thesis includes three chapters. The first two chapters are on theoretical game theory. In both chapters, by mathematical modelling and game theoretical tools, I am predicting the behaviour of the players in some real world issues.
Hoteling-Downs model plays an important role in the modern political interpretations. The first chapter of this study investigates an extension of Hoteling-Downs model to have multi-dimensional strategy space and asymmetric candidates. Chapter 3 looks into the inspection game where the inspections are not the same in the series of sequential inspections. By modelling the game as a series of recursive zero-sum games I find the optimal strategy of the players in the equilibrium.
The forth chapter investigates direct optimization methods for large scale problems. Using Matlab implementations of Genetic and Nelder-Mead algorithms, I compare the efficiency and accuracy of the most famous direct optimization methods for unconstraint optimization problems based on differing number of variables
Evidence of coevolution in multi-objective evolutionary algorithms
This paper demonstrates that simple yet important characteristics of coevolution can occur in evolutionary algorithms when only a few conditions are met. We find that interaction-based fitness measurements such as fitness (linear) ranking allow for a form of coevolutionary dynamics that is observed when 1) changes are made in what solutions are able to interact during the ranking process and 2) evolution takes place in a multi-objective environment. This research contributes to the study of simulated evolution in a at least two ways. First, it establishes a broader relationship between coevolution and multi-objective optimization than has been previously considered in the literature. Second, it demonstrates that the preconditions for coevolutionary behavior are weaker than previously thought. In particular, our model indicates that direct cooperation or competition between species is not required for coevolution to take place. Moreover, our experiments provide evidence that environmental perturbations can drive coevolutionary processes; a conclusion that mirrors arguments put forth in dual phase evolution theory. In the discussion, we briefly consider how our results may shed light onto this and other recent theories of evolution
- …