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Traditional Artificial Intelligence (AI) systems adopted symbolic processing as their main paradigm. Symbolic AI systems have proved effective in handling problems characterized by exact and complete knowledge representation. Unfortunately, these systems have very little power in dealing with imprecise, uncertain and incomplete data and information which significantly contribute to the description of many real world problems, both physical systems and processes as well as mechanisms of decision making. Moreover, there are many situations where the expert domain knowledge (the basis for many symbolic AI systems) is not sufficient for the design of intelligent systems, due to incompleteness of...
The volume LNCS 7269 constitutes the refereed proceedings of the International Symposium on Swarm Intelligence and Differential Evolution, SIDE 2012, held in Zakopane, Poland, in April/May 2012 in conjunction with the 11th International Conference on Artificial Intelligence and Soft Computing, ICAISC 2012 (proceedings published as two-volume set LNAI 7267 and 7268). The 212 revised full papers presented were carefully reviewed and selected from 483 submissions. The volume is divided into two topical parts: proceedings of the 2012 symposium on swarm intelligence and differential evolution and on evolutionary algorithms and their applications.
The LNAI series reports state-of-the-art results in artificial intelligence research, development, education, at a high level and in both printed and electronic form. Enjoying tight cooperation with the R&D community, with numerous individuals, as well as with prestigious organizations and societies, LNAI has grown into the most comprehensive artificial intelligence research forum available. The scope of LNAI spans the whole range of artificial intelligence and intelligent information processing including interdisciplinary topics in a variety of application fields.
This book constitutes the refereed proceedings of the 9th International Conference on Artificial Intelligence and Soft Computing, ICAISC 2008, held in Zakopane, Poland, in June 2008. The 116 revised contributed papers presented were carefully reviewed and selected from 320 submissions. The papers are organized in topical sections on neural networks and their applications, fuzzy systems and their applications, evolutionary algorithms and their applications, classification, rule discovery and clustering, image analysis, speech and robotics, bioinformatics and medical applications, various problems of artificial intelligence, and agent systems.
The two-volume set LNAI 9119 and LNAI 9120 constitutes the refereed proceedings of the 14th International Conference on Artificial Intelligence and Soft Computing, ICAISC 2015, held in Zakopane, Poland in June 2015. The 142 revised full papers presented in the volumes, were carefully reviewed and selected from 322 submissions. These proceedings present both traditional artificial intelligence methods and soft computing techniques. The goal is to bring together scientists representing both areas of research. The first volume covers topics as follows neural networks and their applications, fuzzy systems and their applications, evolutionary algorithms and their applications, classification and estimation, computer vision, image and speech analysis and the workshop: large-scale visual recognition and machine learning. The second volume has the focus on the following subjects: data mining, bioinformatics, biometrics and medical applications, concurrent and parallel processing, agent systems, robotics and control, artificial intelligence in modeling and simulation and various problems of artificial intelligence.
This volume constitutes the proceedings of two collocated international conferences: EUSFLAT-2017 – the 10th edition of the flagship Conference of the European Society for Fuzzy Logic and Technology held in Warsaw, Poland, on September 11–15, 2017, and IWIFSGN’2017 – The Sixteenth International Workshop on Intuitionistic Fuzzy Sets and Generalized Nets, held in Warsaw on September 13–15, 2017. The conferences were organized by the Systems Research Institute, Polish Academy of Sciences, Department IV of Engineering Sciences, Polish Academy of Sciences, and the Polish Operational and Systems Research Society in collaboration with the European Society for Fuzzy Logic and Technology (E...
This book constitutes the refereed proceedings of the 8th International Conference on Artificial Intelligence and Soft Computing, ICAISC 2006, held in Zakopane, Poland, in June 2006. The 128 revised contributed papers presented are organized in topical sections on neural networks and their applications, fuzzy systems and their applications, evolutionary algorithms and their applications, rough sets, classification and clustering, image analysis and robotics, bioinformatics and medical applications, various problems of artificial intelligence.
Fact finding in judicial proceedings is a dynamic process. This collection of papers considers whether computational methods or other formal logical methods developed in disciplines such as artificial intelligence, decision theory, and probability theory can facilitate the study and management of dynamic evidentiary and inferential processes in litigation. The papers gathered here have several epicenters, including (i) the dynamics of judicial proof, (ii) the relationship between artificial intelligence or formal analysis and "common sense," (iii) the logic of factual inference, including (a) the relationship between causality and inference and (b) the relationship between language and factual inference, (iv) the logic of discovery, including the role of abduction and serendipity in the process of investigation and proof of factual matters, and (v) the relationship between decision and inference.
Advances in Computational Intelligence and Learning: Methods and Applications presents new developments and applications in the area of Computational Intelligence, which essentially describes methods and approaches that mimic biologically intelligent behavior in order to solve problems that have been difficult to solve by classical mathematics. Generally Fuzzy Technology, Artificial Neural Nets and Evolutionary Computing are considered to be such approaches. The Editors have assembled new contributions in the areas of fuzzy sets, neural sets and machine learning, as well as combinations of them (so called hybrid methods) in the first part of the book. The second part of the book is dedicated to applications in the areas that are considered to be most relevant to Computational Intelligence.