Advanced Intelligent Paradigms in Computer Games by Norio Baba, Hisashi Handa

By Norio Baba, Hisashi Handa

This ebook provides a pattern of the newest examine in regards to the program of computational intelligence strategies and web expertise in machine video games. The contents include:

  • COMMONS online game in clever environment
  • Adaptive new release of dilemma-based interactive narratives
  • Computational intelligence in racing games
  • Evolutionary algorithms for board video game gamers with area knowledge
  • The ChessBrain project
  • Electronic industry games
  • EVE’s entropy
  • Capturing participant amusement in machine games

This e-book is directed to researchers, working towards engineers/scientists and students.

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Additional info for Advanced Intelligent Paradigms in Computer Games

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It is necessary Adaptive Generation of Dilemma-based Interactive Narratives 31 to plan for dilemmas which have a high dramatic interest, although this will largely depend on the current user. The user model is discussed in the next section. 9 The User Model The user of an interactive drama system should be modelled rather than controlled. The story should adapt to the user’s interactions rather than forcing the user to follow a particular storyline. The user model will ideally be used to identify which dilemmas are going to be most conflicting and dramatically interesting for the current user.

Here, an attractive person is in love with someone less attractive. In a soap world (where looks are very important) the less attractive character will fall in reciprocal love with the more attractive Once a plan for a dilemma has been found, the system will execute this dilemma. In order to do so, the current state must be updated in accordance with each action in the plan. These actions are shown to the user, so that they understand the dilemma and will consequently be more interested in it. 34 H.

Tanev [17] developed an anticipatory control algorithm for an R/C racing simulator, and used evolutionary computation to tune the parameters of this algorithm for optimal lap time. Chaperot and Fyfe [18] evolved neural network controllers for minimal lap time in a 3D motocross game, and we previously ourselves investigated which controller architectures are best suited for such optimisation in a simple racing game [19]. Sometimes optimisation is multiobjective, as in our previous work on optimising controllers for performance on particular racing tracks versus robustness in driving on new tracks [20].

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