TAILIEUCHUNG - Biologically Inspired Artificial Intelligence for Computer Games

As game developers a few years from now, we may look back at current generation AI with astonishment and possibly with a hint of nostalgia. We will notice the extreme simplicity of the systems and behaviours we created, asking ourselves whether it was in fact by design or more by necessity. More importantly, we will be surprised by the amount of time taken to prototype such AI. These classical game AI techniques (such as finite-state machines or scripts) appeal to us game developers because they can be easily controlled, but they suffer from this very same property; the content creators. | Biologically Inspired Artificial Intelligence for Computer Games Darryl Charles Colin Fyfe Daniel Livingstone Stephen McGlinchey IGI Publishing Biologically Inspired Artificial Intelligence for Computer Games Darryl Charles University of Ulster Ireland Colin Fyfe University of Paisley UK Daniel Livingstone University of Paisley UK Stephen McGlinchey University of Paisley UK I Medical Information Science MEDICAL INFORMATION SCIENCE REFERENCE Hershey New York Acquisition Editor Kristin Klinger Senior Managing Editor Jennifer Neidig Managing Editor Sara Reed Development Editor Kristin Roth Copy Editor Ashlee Kunkel Typesetter Jamie Snavely Cover Design Lisa Tosheff Printed at Yurchak Printing Inc. Published in the United States of America by IGI Publishing an imprint of IGI Global 701 E. Chocolate Avenue Hershey PA 17033 Tel 7i7-533-8845 Fax 717-533-8661 E-mail cust@ Web site http and in the United Kingdom by IGI Publishing an imprint of IGI Global 3 Henrietta Street Covent Garden London WC2E 8LU Tel 44 20 7240 0856 Fax 44 20 7379 0609 Web site http Copyright 2008 by IGI Global. All rights reserved. No part of this book may be reproduced in any form or by any means electronic or mechanical including photocopying without written permission from the publisher. Product or company names used in this book are for identification purposes only. Inclusion of the names of the products or companies does not indicate a claim of ownership by IGI Global of the trademark or registered trademark. Library of Congress Cataloging-in-Publication Data Biologically inspired artificial intelligence for computer games Darryl Charles Colin Fyfe Daniel Livingstone Stephen McGlinchey editors. p. cm. Summary This book examines modern artificial intelligence to display how it may be applied to computer games. It spans the divide that exists between the academic research community working with advanced artificial intelligence and the games .

• Sinh học
• Biological Neural Networks
• Neural Network
• Artificial Neural
• Delta Rule
• The Backpropagation
• Hebbian Learning
• Neural Networks
• Aided Diagnosis
• Biomedical Applications
• Biological Research
• Cell Responses
• BMC Bioinformatics
• Quantitative real time PCR
• Biological processes
• Convolution neural networks
• Deep neural networks
• Artificial neural network
• Gene regulatory networks
• Prediction of response
• Clinical trial
• Group Lasso
• Deep learning
• Convolutional networks
• Object detection
• Basic biology
• The NeuroProcessor
• Neuronal recording
• NeuroProcessor spike sorting
• MEA on Chip
• Integrated front
• Biological nitrogen fixation
• Artificial neural networks
• Protein classification
• Azospirillum brasilense
• Operon draTGB
• Histone marks
• Chromatin modifications
• Epigenetic signatures
• Journal of Computer science
• Acute stress modeled
• Adaptive temporal–causal network model
• Network Oriented modeling methodology
• Keeping homeostasis