The purpose of this computer program is to allow the user to construct, train and test differenttypes of Artificial neural networks. By implementing the concepts of templates, inheritance andderived classes from C++ object oriented programming, the necessity for declaring multiple largestructures and duplicate attributes is reduced. Utilizing dynamic binding and memory allocationafforded by C++, the user can choose to develop four separate types of neural networks:
Tic Tac Toe程序。可以供一到兩個玩家使用。程序中使用了visual basic 計時器，所以每一個步驟都有時間限制。此外，計算機可是一個有簡單智能的對手，他不但不會隨便出手，反而還要竭力贏了你才罷休。
Tic Tac Toe program. One or two players. It uses the visual basic timer, so each move has time limit. Simple Artificial intelligence: computer does not play randomly, but "tries" to win and stop you from winning.
a Java toolkit for training, testing, and applying Bayesian Network Classifiers. Implemented classifiers have been shown to perform well in a variety of Artificial intelligence, machine learning, and data mining applications.
Learning Kernel Classifiers: Theory and Algorithms, Introduction This chapter introduces the general problem of machine learning and how it relates to statistical inference. 1.1 The Learning Problem and (Statistical) Inference It was only a few years after the introduction of the first computer that one of man’s greatest dreams seemed to be realizable—Artificial intelligence. Bearing in mind that in the early days the most powerful computers had much less computational power than a cell phone today, it comes as no surprise that much theoretical research on the potential of machines’ capabilities to learn took place at this time. This becomes a computational problem as soon as the dataset gets larger than a few hundred examples.
This paper presents an interactive technique that
produces static hairstyles by generating individual hair strands
of the desired shape and color, subject to the presence of gravity
and collisions. A variety of hairstyles can be generated by
adjusting the wisp parameters, while the deformation is solved
efficiently, accounting for the effects of gravity and collisions.
Wisps are generated employing statistical approaches. As for
hair deformation, we propose a method which is based on
physical simulation concepts but is simplified to efficiently
solve the static shape of hair. On top of the statistical wisp
model and the deformation solver, a constraint-based styler
is proposed to model Artificial features that oppose the natural
flow of hair under gravity and hair elasticity, such as a hairpin.
Our technique spans a wider range of human hairstyles than
previously proposed methods, and the styles generated by this
technique are fairly realistic.
《多傳感器數(shù)據(jù)融合手冊》
《Handbook of Multisensor Data Fusion》
作者: David L. Hall
定價: USD 199.95
出版社: CRC
出版年: 2001-06-20
簡介 · · · · · ·
Multisensor data fusion is an emerging technology with important applications in both the military and civilian sectors, such as target recognition, robotics, medical diagnostics, and "smart" buildings. It draws on techniques from wide-ranging disciplines, including Artificial intelligence, pattern recognition, and statistical estimation. This handbook is an up-to-date, comprehensive resource for data fusion system designers and researchers. Top experts in the field lead readers from a basic introduction and survey of data fusion technology to advanced mathematics and theory and to some very practical advice for systems implementers.
aiNet application is a very powerful and a very simple tool for solving the problems which are usually solved with Artificial neural networks (ANN). All possible tests we had run proved that the results obtained with aiNet are at least as good as the results obtained with some other ANNs. Let us state some of aiNet抯 features.
(c) aiNet 1995-1997
The MDP toolbox proposes functions related to the resolution of discrete-time Markov Decision Process : finite horizon, value iteration, policy iteration, linear programming algorithms with some variants.
The functions (m-functions) were developped with MATLAB v6.0 (one of the functions requires the Mathworks Optimization Toolbox) by the decision team of the Biometry and Artificial Intelligence Unit of INRA Toulouse (France).
The version 2.0 (February 2005) handles sparse matrices and contains an example
Proceedings of Practice of Interesting Algorithms 2007
The editor assumes no responsibility for the accuracy, completeness or usefulness of
the information disclosed in this volume. Unauthorized use might infringe on
privately owned patents of publication right. Please contact the individual authors for
permission to reprint or otherwise use information from their papers.
First edition 2007
Publication Planned by Prof. Wenxin Li
Edited by Yili Zhao
All rights reserved
by
Artificial Intelligence Laboratory, Peking University
June 26, 2007
Tricks of the Windows Game Programmin Gurus, 2E takes the reader through Win32 programming, covering all the major components of DirectX including DirectDraw, DirectSound, DirectInput (including Force Feedback), and DirectMusic. Andre teaches the reader 2D graphics and rasterization techniques. Finally, Andre provides the most intense coverage of game algorithms, multithreaded programming, Artificial intelligence (including fuzzy logic, neural nets, and genetic algorithms), and physics modeling you have ever seen in a game book.
