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Complex social and behavioral system...

Castiglione, Filippo.

Complex social and behavioral systemsgame theory and agent-based models /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Complex social and behavioral systemsedited by Marilda Sotomayor, David Perez-Castrillo, Filippo Castiglione.
Reminder of title:	game theory and agent-based models /
other author:	Sotomayor, Marilda.
Published:	New York, NY :Springer US :2020.
Description:	xxiv, 939 p. :ill. (some col.), digital ;24 cm.
Contained By:	Springer Nature eReference
Subject:	Game theory.
Online resource:	https://doi.org/10.1007/978-1-0716-0368-0
ISBN:	9781071603680$q(electronic bk.)

Complex social and behavioral systemsgame theory and agent-based models /
Complex social and behavioral systemsgame theory and agent-based models /[electronic resource] :edited by Marilda Sotomayor, David Perez-Castrillo, Filippo Castiglione. - New York, NY :Springer US :2020. - xxiv, 939 p. :ill. (some col.), digital ;24 cm. - Encyclopedia of complexity and systems science series. - Encyclopedia of complexity and systems science series..

Part I Game Theory -- Game Theory, Introduction to -- Cooperative Games -- Cooperative Games (von Neumann-Morgenstern Stable Sets) -- Cost Sharing -- Fair Division -- Two-Sided Matching Models -- Networks and Stability -- Market Games and Clubs -- Voting -- Voting Procedures, Complexity of -- Social Choice Theory -- Static Games -- Game Theory and Strategic Complexity -- Zero-Sum Two Person Games -- Differential Games -- Bayesian Games: Games with Incomplete Information -- Correlated Equilibria and Communication in Games -- Signaling Games -- Auctions -- Repeated Games with Complete Information -- Repeated Games with Incomplete Information -- Reputation Effects -- Learning in Games -- Dynamic Games with an Application to Climate Change Models -- Evolutionary Game Theory -- Stochastic Games -- Implementation Theory -- Mechanism Design -- Market Design -- Principal-Agent Models -- Inspection Games -- Experimental Games -- Part II Agent Based Modeling and Simulation -- Agent Based Modeling and Simulation, Introduction to -- Agent Based Modeling and Simulation -- Embodied and Situated Agents, Adaptive Behavior in -- Swarm Intelligence -- Agent-Based Modeling and Artificial Life -- Interaction Based Computing in Physics -- Cellular Automaton Modeling of Tumor Invasion -- Agent Based Computational Economics -- Social Phenomena Simulation -- Computer Graphics and Games, Agent Based Modeling in -- Agent Based Modeling, Large Scale Simulations -- Agent Based Modeling for Multi-scale systems -- Agent Based Modeling, Mathematical Formalism for -- Logic and Geometry of Agents in Agent-Based Modeling -- Agent-Based Modeling and Computer.

This volume in the Encyclopedia of Complexity and Systems Science, Second Edition, combines the main features of Game Theory, covering most of the fundamental theoretical aspects under the cooperative and non-cooperative approaches, with the procedures of Agent-Based Modeling for studying complex systems composed of a large number of interacting entities with many degrees of freedom. In Game Theory, the cooperative approach focuses on the possible outcomes of the decision-makers' interaction by abstracting from the "rational" actions or decisions that may lead to these outcomes. The non-cooperative approach focuses on the actions that the decision-makers can take. As John von Neumann and Oskar Morgenstern argued in their path-breaking book of 1944 entitled Theory of Games and Economic Behavior, most economic questions should be analyzed as games. The models of game theory are abstract representations of a number of real-life situations and have applications to economics, political science, computer science, evolutionary biology, social psychology, and law among others. Agent-Based Modeling (ABM) is a relatively new computational modeling paradigm which aims to construct the computational counterpart of a conceptual model of the system under study on the basis of discrete entities (i.e., the agent) with some properties and behavioral rules, and then to simulate them in a computer to mimic the real phenomena. Given the relative immaturity of this modeling paradigm, and the broad spectrum of disciplines in which it is applied, a clear cut and widely accepted definition of high level concepts of agents, environment, interactions and so on, is still lacking. This volume explores the state-of-the-art in the development of a real ABM ontology to address the epistemological issues related to this emerging paradigm for modeling complex systems.

ISBN: 9781071603680$q(electronic bk.)

Standard No.: 10.1007/978-1-0716-0368-0doiSubjects--Topical Terms:

182956
Game theory.

LC Class. No.: QA269

Dewey Class. No.: 519.3

Complex social and behavioral systemsgame theory and agent-based models /
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520 $a This volume in the Encyclopedia of Complexity and Systems Science, Second Edition, combines the main features of Game Theory, covering most of the fundamental theoretical aspects under the cooperative and non-cooperative approaches, with the procedures of Agent-Based Modeling for studying complex systems composed of a large number of interacting entities with many degrees of freedom. In Game Theory, the cooperative approach focuses on the possible outcomes of the decision-makers' interaction by abstracting from the "rational" actions or decisions that may lead to these outcomes. The non-cooperative approach focuses on the actions that the decision-makers can take. As John von Neumann and Oskar Morgenstern argued in their path-breaking book of 1944 entitled Theory of Games and Economic Behavior, most economic questions should be analyzed as games. The models of game theory are abstract representations of a number of real-life situations and have applications to economics, political science, computer science, evolutionary biology, social psychology, and law among others. Agent-Based Modeling (ABM) is a relatively new computational modeling paradigm which aims to construct the computational counterpart of a conceptual model of the system under study on the basis of discrete entities (i.e., the agent) with some properties and behavioral rules, and then to simulate them in a computer to mimic the real phenomena. Given the relative immaturity of this modeling paradigm, and the broad spectrum of disciplines in which it is applied, a clear cut and widely accepted definition of high level concepts of agents, environment, interactions and so on, is still lacking. This volume explores the state-of-the-art in the development of a real ABM ontology to address the epistemological issues related to this emerging paradigm for modeling complex systems.
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