Norio Baba – författare

The evolution of technologies has greatly changed the basic structure of our industry and nature of our daily lives. Industries which did not exist several decades ago have made remarkable progress in recent years and ?ourished. One of the most typical examples is the computer game industry. This book presents a sample of the most recent research concerning the application of computational intelligence techniques and internet technology in computer games. This book contains eight chapters. The ?rst chapter, by N. Baba and H. Handa, is on utilization of evolutionary algorithms to increase excitement of the COMMONS GAME. It is shown that the original COMMONS GAME which is one of the most popular environmental games has been made much more exciting by the intelligent utilization of the two evolutionary algorithms. The second chapter, by H. Barber and D. Kudenko, is on adaptive g- eration of dilemma-based interactive narratives. In this chapter, they present an interactive narrative generator that can create story lines that incorporate dilemmas to add dramatic tension. They also brie?y touch upon the pos- bility that their work could provide a useful tool for making dramatically interesting game playing possible. The third chapter, by J. Tongelius, S.M. Lucas, and R.D. Nardi, is on computational intelligence (CI) in racing games. The authors suggest that CI techniques can be used for various purposes such as controller evolution for the racing and track evolution for a pro?cient player.

The evolution of technologies has greatly changed the basic structure of our industry and nature of our daily lives. Industries which did not exist several decades ago have made remarkable progress in recent years and ?ourished. One of the most typical examples is the computer game industry. This book presents a sample of the most recent research concerning the application of computational intelligence techniques and internet technology in computer games. This book contains eight chapters. The ?rst chapter, by N. Baba and H. Handa, is on utilization of evolutionary algorithms to increase excitement of the COMMONS GAME. It is shown that the original COMMONS GAME which is one of the most popular environmental games has been made much more exciting by the intelligent utilization of the two evolutionary algorithms. The second chapter, by H. Barber and D. Kudenko, is on adaptive g- eration of dilemma-based interactive narratives. In this chapter, they present an interactive narrative generator that can create story lines that incorporate dilemmas to add dramatic tension. They also brie?y touch upon the pos- bility that their work could provide a useful tool for making dramatically interesting game playing possible. The third chapter, by J. Tongelius, S.M. Lucas, and R.D. Nardi, is on computational intelligence (CI) in racing games. The authors suggest that CI techniques can be used for various purposes such as controller evolution for the racing and track evolution for a pro?cient player.

The evolution of technologies has greatly changed the basic structure of our industry and nature of our daily lives. Industries which did not exist several decades ago have made remarkable progress in recent years and ?ourished. One of the most typical examples is the computer game industry. This book presents a sample of the most recent research concerning the application of computational intelligence techniques and internet technology in computer games. This book contains eight chapters. The ?rst chapter, by N. Baba and H. Handa, is on utilization of evolutionary algorithms to increase excitement of the COMMONS GAME. It is shown that the original COMMONS GAME which is one of the most popular environmental games has been made much more exciting by the intelligent utilization of the two evolutionary algorithms. The second chapter, by H. Barber and D. Kudenko, is on adaptive g- eration of dilemma-based interactive narratives. In this chapter, they present an interactive narrative generator that can create story lines that incorporate dilemmas to add dramatic tension. They also brie?y touch upon the pos- bility that their work could provide a useful tool for making dramatically interesting game playing possible. The third chapter, by J. Tongelius, S.M. Lucas, and R.D. Nardi, is on computational intelligence (CI) in racing games. The authors suggest that CI techniques can be used for various purposes such as controller evolution for the racing and track evolution for a pro?cient player.

The most powerful computers in the world are not only used for scientific research, defence, and business, but also in game playing. Recent advances in computational intelligence paradigms have generated tremendous interest among researchers in the theory and implementation of games.

The most powerful computers in the world are not only used for scientific research, defence, and business, but also in game playing. Computer games are a multi-billion dollar industry. Recent advances in computational intelligence paradigms have generated tremendous interest among researchers in the theory and implementation of games. Game theory is a branch of operational research dealing with decision theory in a competitive situation. Game theory involves the mathematical calculations and heuristics to optimize the efficient lines of play. This book presents a sample of the most recent research on the application of computational intelligence techniques in games. This book contains 7 chapters. The first chapter, by Chen, Fanelli, Castellano, and Jain, is an introduction to computational intelligence paradigms. It presents the basics of the main constituents of compu­ tational intelligence paradigms including knowledge representation, probability-based approaches, fuzzy logic, neural networks, genetic algorithms, and rough sets. In the second chapter, Chellapilla and Fogel present the evolution of a neural network to play checkers without human expertise. This chapter focuses on the use of a population of neural networks, where each network serves as an evaluation function to describe the quality of the current board position. After only a little more than 800 generations, the evolutionary process has generated a neural network that can play checkers at the expert level as designated by the u.s. Chess Federation rating system. The program developed by the authors has also competed well against commercially available software.