Game Dynamics
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Game Dynamics
This book offers a compendium of best practices in game dynamics. It covers a wide range of dynamic game elements ranging from player behavior over artificial intelligence to procedural content generation. Such dynamics make virtual worlds more lively and realistic and they also create the potential for moments of amazement and surprise. In many cases, game dynamics are driven by a combination of random seeds, player records and procedural algorithms. Games can even incorporate the player’s real-world behavior to create dynamic responses. The best practices illustrate how dynamic elements improve the user experience and increase the replay value. The book draws upon interdisciplinary approaches; researchers and practitioners from Game Studies, Computer Science, Human-Computer Interaction, Psychology and other disciplines will find this book to be an exceptional resource of both creative inspiration and hands-on process knowledge.
Evolutionary Game Dynamics
Author: American Mathematical Society. Short Course
language: en
Publisher: American Mathematical Soc.
Release Date: 2011-10-27
This volume is based on lectures delivered at the 2011 AMS Short Course on Evolutionary Game Dynamics, held January 4-5, 2011 in New Orleans, Louisiana. Evolutionary game theory studies basic types of social interactions in populations of players. It combines the strategic viewpoint of classical game theory (independent rational players trying to outguess each other) with population dynamics (successful strategies increase their frequencies). A substantial part of the appeal of evolutionary game theory comes from its highly diverse applications such as social dilemmas, the evolution of language, or mating behaviour in animals. Moreover, its methods are becoming increasingly popular in computer science, engineering, and control theory. They help to design and control multi-agent systems, often with a large number of agents (for instance, when routing drivers over highway networks or data packets over the Internet). While these fields have traditionally used a top down approach by directly controlling the behaviour of each agent in the system, attention has recently turned to an indirect approach allowing the agents to function independently while providing incentives that lead them to behave in the desired way. Instead of the traditional assumption of equilibrium behaviour, researchers opt increasingly for the evolutionary paradigm and consider the dynamics of behaviour in populations of agents employing simple, myopic decision rules.
Game Theory for Wireless Communications and Networking
This comprehensive technical guide explains game theory basics, architectures, protocols, security, models, open research issues, and cutting-edge advances and applications. Describing how to employ game theory in infrastructure-based wireless networks and multihop networks to reduce power consumption, it facilitates quick and easy reference to related optimization and algorithm methodologies. The book explains how to apply the game theoretic model to address resource allocation, congestion control, attacks, routing, energy management, packet forwarding, and MAC.