Artificial Intelligence Research and Development by M. Polit, T. Talbert, B. Lopez, J. Melendez

By M. Polit, T. Talbert, B. Lopez, J. Melendez

Man made Intelligence (AI) types a vital department of computing device technological know-how. the sphere coated via AI is multiform and gathers matters as a variety of because the engineering of information, the automated therapy of the language, the learning and the platforms multiagents, to cite just some of them. The background of AI knew a number of sessions of evolution passing from classes of doubt at very fertile sessions. AI is now in its adulthood and didn't stay an remoted box of machine technology, yet approached numerous fields like facts, information research, linguistics and cognitive psychology or databases. AI is concentrated on supplying strategies to genuine lifestyles difficulties and is used now in regimen in medication, economics and armed forces or process video game. This ebook specializes in matters together with computing device studying, Reasoning, Neural Networks, desktop imaginative and prescient, making plans and Robotics and Multiagent structures. all of the papers accumulated during this quantity are of curiosity to any desktop scientist or engineer drawn to AI.IOS Press is a global technology, technical and scientific writer of high quality books for teachers, scientists, and execs in all fields. many of the parts we post in: -Biomedicine -Oncology -Artificial intelligence -Databases and knowledge platforms -Maritime engineering -Nanotechnology -Geoengineering -All features of physics -E-governance -E-commerce -The wisdom economic climate -Urban reviews -Arms keep watch over -Understanding and responding to terrorism -Medical informatics -Computer Sciences

Show description

Read or Download Artificial Intelligence Research and Development PDF

Best intelligence & semantics books

Evolutionary Computation in Practice

This ebook is loaded with examples during which laptop scientists and engineers have used evolutionary computation - courses that mimic typical evolution - to unravel genuine difficulties. They aren t summary, mathematically in depth papers, yet debts of fixing vital difficulties, together with suggestions from the authors on easy methods to stay away from universal pitfalls, maximize the effectiveness and potency of the quest technique, and plenty of different useful feedback.

Feedforward Neural Network Methodology (Springer Series in Statistics)

This decade has visible an explosive progress in computational pace and reminiscence and a fast enrichment in our figuring out of synthetic neural networks. those components offer structures engineers and statisticians being able to construct types of actual, monetary, and information-based time sequence and signs.

Artificial Intelligence for Humans, Volume 2: Nature-Inspired Algorithms

Nature could be a nice resource of thought for synthetic intelligence algorithms simply because its expertise is significantly extra complex than our personal. between its wonders are robust AI, nanotechnology, and complicated robotics. Nature can consequently function a consultant for real-life challenge fixing. during this e-book, you are going to come upon algorithms stimulated by way of ants, bees, genomes, birds, and cells that supply functional equipment for plenty of forms of AI occasions.

Additional info for Artificial Intelligence Research and Development

Example text

1. Logistic Regression (LR) The Logistic Regression (LR) is part of the models in which the response variable is qualitative, for example, the occurrence or not of a certain event or the belong or not to a certain category. In this work Binary Logistic Regression is used to identify which variables better explain every class by using as a binary response variable the dummy YC. 40 K. Gibert et al. / A Comparative Analysis of Different Classes-Interpretation Support Techniques The explanatory variables could be quantitative or qualitative if these are correspondingly treated and the result is a model for the probability of an object of being in C or not [14].

However, in other areas such as car painting in the automotive industry, no such large databases exist, and it will takes a long time to build them due to cost and time considerations. Therefore the precision nowadays required by the color automotive industry cannot be achieved with existing tools. This work presents an innovative procedure using Support Vector Machines as a decision-making tool in the task of color adjustment in the automotive industry. This kind of soft computing technique has been successfully used for complex problems similar to that already described, allowing extraction of knowledge from databases and prediction of results in new situations.

Firstly, a personal computer containing both case-base and CBR software searches previous matches for the best match by using nearest neighbor retrieval. Next, previous matches are iteratively adjusted by a software to produce matches for the new standard. This software is based on the equations of Kubelka-Munk, among whose suppositions are that the proportions of absorption and scattering of a pigment mixture are a linear combination of the proportions of each pigment separately. As well as the difficulty in measuring the parameters involved, these assumptions make the use of this tool difficult for final color adjustment.

Download PDF sample

Rated 4.05 of 5 – based on 23 votes