Machine Learning Proceedings 1991

Machine Learning Proceedings 1991
Author :
Publisher : Morgan Kaufmann
Total Pages : 682
Release :
ISBN-10 : 9781483298177
ISBN-13 : 1483298175
Rating : 4/5 (77 Downloads)

Synopsis Machine Learning Proceedings 1991 by : Lawrence A. Birnbaum

Machine Learning

Machine Learning Proceedings 1993

Machine Learning Proceedings 1993
Author :
Publisher : Morgan Kaufmann
Total Pages : 361
Release :
ISBN-10 : 9781483298627
ISBN-13 : 1483298620
Rating : 4/5 (27 Downloads)

Synopsis Machine Learning Proceedings 1993 by : Lawrence A. Birnbaum

Machine Learning Proceedings 1993

Machine Learning Proceedings 1994

Machine Learning Proceedings 1994
Author :
Publisher : Morgan Kaufmann
Total Pages : 398
Release :
ISBN-10 : 9781483298184
ISBN-13 : 1483298183
Rating : 4/5 (84 Downloads)

Synopsis Machine Learning Proceedings 1994 by : William W. Cohen

Machine Learning Proceedings 1994

Machine Learning Proceedings 1992

Machine Learning Proceedings 1992
Author :
Publisher : Morgan Kaufmann
Total Pages : 497
Release :
ISBN-10 : 9781483298535
ISBN-13 : 1483298531
Rating : 4/5 (35 Downloads)

Synopsis Machine Learning Proceedings 1992 by : Peter Edwards

Machine Learning Proceedings 1992

Machine Learning Proceedings 1995

Machine Learning Proceedings 1995
Author :
Publisher : Morgan Kaufmann
Total Pages : 606
Release :
ISBN-10 : 9781483298665
ISBN-13 : 1483298663
Rating : 4/5 (65 Downloads)

Synopsis Machine Learning Proceedings 1995 by : Armand Prieditis

Machine Learning Proceedings 1995

Machine Learning: ECML-93

Machine Learning: ECML-93
Author :
Publisher : Springer Science & Business Media
Total Pages : 492
Release :
ISBN-10 : 3540566023
ISBN-13 : 9783540566021
Rating : 4/5 (23 Downloads)

Synopsis Machine Learning: ECML-93 by : Pavel B. Brazdil

This volume contains the proceedings of the Eurpoean Conference on Machine Learning (ECML-93), continuing the tradition of the five earlier EWSLs (European Working Sessions on Learning). The aim of these conferences is to provide a platform for presenting the latest results in the area of machine learning. The ECML-93 programme included invited talks, selected papers, and the presentation of ongoing work in poster sessions. The programme was completed by several workshops on specific topics. The volume contains papers related to all these activities. The first chapter of the proceedings contains two invited papers, one by Ross Quinlan and one by Stephen Muggleton on inductive logic programming. The second chapter contains 18 scientific papers accepted for the main sessions of the conference. The third chapter contains 18 shorter position papers. The final chapter includes three overview papers related to the ECML-93 workshops.

Mathematical Foundations of Computer Science 1986

Mathematical Foundations of Computer Science 1986
Author :
Publisher : Springer Science & Business Media
Total Pages : 810
Release :
ISBN-10 : 3540167838
ISBN-13 : 9783540167839
Rating : 4/5 (38 Downloads)

Synopsis Mathematical Foundations of Computer Science 1986 by : Jozef Gruska

Uncertainty in Knowledge Bases

Uncertainty in Knowledge Bases
Author :
Publisher : Springer Science & Business Media
Total Pages : 630
Release :
ISBN-10 : 3540543465
ISBN-13 : 9783540543466
Rating : 4/5 (65 Downloads)

Synopsis Uncertainty in Knowledge Bases by : Bernadette Bouchon-Meunier

One out of every two men over eigthy suffers from carcinoma of the prostate.It is discovered incidentally in many patients with an alleged benign prostatic hyperplasia. In treating patients, the authors make clear that primary radical prostatectomy is preferred over transurethral resection due to the lower complication rate.

Machine Learning: From Theory to Applications

Machine Learning: From Theory to Applications
Author :
Publisher : Springer Science & Business Media
Total Pages : 292
Release :
ISBN-10 : 3540564837
ISBN-13 : 9783540564836
Rating : 4/5 (37 Downloads)

Synopsis Machine Learning: From Theory to Applications by : Stephen J. Hanson

This volume includes some of the key research papers in the area of machine learning produced at MIT and Siemens during a three-year joint research effort. It includes papers on many different styles of machine learning, organized into three parts. Part I, theory, includes three papers on theoretical aspects of machine learning. The first two use the theory of computational complexity to derive some fundamental limits on what isefficiently learnable. The third provides an efficient algorithm for identifying finite automata. Part II, artificial intelligence and symbolic learning methods, includes five papers giving an overview of the state of the art and future developments in the field of machine learning, a subfield of artificial intelligence dealing with automated knowledge acquisition and knowledge revision. Part III, neural and collective computation, includes five papers sampling the theoretical diversity and trends in the vigorous new research field of neural networks: massively parallel symbolic induction, task decomposition through competition, phoneme discrimination, behavior-based learning, and self-repairing neural networks.

Robot Colonies

Robot Colonies
Author :
Publisher : Springer Science & Business Media
Total Pages : 150
Release :
ISBN-10 : 9781475764512
ISBN-13 : 1475764510
Rating : 4/5 (12 Downloads)

Synopsis Robot Colonies by : Ronald C. Arkin

Robots in groups or colonies can exhibit an enormous variety and richness of behaviors which cannot be observed with singly autonomous systems. Of course, this is analogous to the amazing variety of group animal behaviors which can be observed in nature. In recent years more and more investigators have started to study these behaviors. The studies range from classifications and taxonomies of behaviors, to development of architectures which cause such group activities as flocking or swarming, and from emphasis on the role of intelligent agents in such groups to studies of learning and obstacle avoidance. There used to be a time when many robotics researchers would question those who were interested in working with teams of robots: `Why are you worried about robotic teams when it's hard enough to just get one to work?'. This issue responds to that question. Robot Colonies provides a new approach to task problem-solving that is similar in many ways to distributed computing. Multiagent robotic teams offer the possibility of spatially distributed parallel and concurrent perception and action. A paradigm shift results when using multiple robots, providing a different perspective on how to carry out complex tasks. New issues such as interagent communications, spatial task distribution, heterogeneous or homogeneous societies, and interference management are now central to achieving coordinated and productive activity within a colony. Fortunately mobile robot hardware has evolved sufficiently in terms of both cost and robustness to enable these issues to be studied on actual robots and not merely in simulation. Robot Colonies presents a sampling of the research in this field. While capturing a reasonable representation of the most important work within this area, its objective is not to be a comprehensive survey, but rather to stimulate new research by exposing readers to the principles of robot group behaviors, architectures and theories. Robot Colonies is an edited volume of peer-reviewed original research comprising eight invited contributions by leading researchers. This research work has also been published as a special issue of Autonomous Robots (Volume 4, Number 1).