Hybrid Artificial Intelligence Systems

This book constitutes the proceedings of the 5th International Conference on Hybrid Artificial Intelligent Systems, held in San Sebastian, Spain, in June 2010.

This book constitutes the refereed proceedings of the 16th International Conference on Hybrid Artificial Intelligent Systems, HAIS 2021, held in Bilbao, Spain, in September 2021. The 44 full and 11 short papers presented in this book were carefully reviewed and selected from 81 submissions. The papers are grouped into these topics: data mining, knowledge discovery and big data; bio-inspired models and evolutionary computation; learning algorithms; visual analysis and advanced data processing techniques; machine learning applications; hybrid intelligent applications; deep learning applications; and optimization problem applications.

This volume constitutes the proceedings of the Third International Workshop on Hybrid Artificial Intelligence Systems, HAIS 2008, held in Burgos, Spain, during September 24-26, 2008. The 93 papers presented, together with 4 invited talks, were carefully reviewed and selected from 280 submissions. The topics covered are agents and multi-agent systems; evolutionary computation; connectionist models; optimization sysetms; fuzzy logic systems; classification and classifiers; cluster analysis; video and image analysis; learning systems, algorithms and applications; hybrid systems based on negotiation and social network modelling; real world applications of HAIS under uncertainty; hybrid intelligent systems for multi-robot and multi-agent systems; applications of hybrid artificial intelligence in bioinformatics; and novel approaches to genetic fuzzy systems.

This carefully edited book combines symbolic and sub-symbolic techniques to construct more robust and reliable problem solving models. This volume focused on "Hybrid Artificial Intelligence Systems" contains a collection of papers that were presented at the 2nd International Workshop on Hybrid Artificial Intelligence Systems, held in 12 - 13 November, 2007, Salamanca, Spain.

This volume constitutes the proceedings of the 10th International Conference on Hybrid Artificial Intelligent Systems, HAIS 2015, held Bilbao, Spain, June 2014. The 60 papers published in this volume were carefully reviewed and selected from 190 submissions. They are organized in topical sections such as data mining and knowledge discovery; video and image analysis; bio-inspired models and evolutionary computation; learning algorithms; hybrid intelligent systems for data mining and applications; classification and cluster analysis, HAIS applications.

This volume constitutes the refereed proceedings of the 14th International Conference on Hybrid Artificial Intelligent Systems, HAIS 2019, held in León, Spain, in September 2019. The 64 full papers published in this volume were carefully reviewed and selected from 134 submissions. They are organized in the following topical sections: data mining, knowledge discovery and big data; bio-inspired models and evolutionary computation; learning algorithms; visual analysis and advanced data processing techniques; data mining applications; and hybrid intelligent applications.

This volume constitutes the proceedings of the 8th International Conference on Hybrid Artificial Intelligent Systems, HAIS 2013, held in Salamanca, Spain, in September 2013. The 68 papers published in this volume were carefully reviewed and selected from 218 submissions. They are organized in topical sessions on Agents and Multi Agents Systems; HAIS Applications; Classification and Cluster Analysis; Data Mining and Knowledge Discovery; Video and Image Analysis; Bio-inspired Models and Evolutionary Computation; Learning Algorithms; Systems, MAN, and Cybernetics; Hybrid Intelligent Systems for Data Mining and Applications; Metaheuristics for Combinatorial Optimization and Modelling Complex Systems.

This book is intended for specialists as well as students and graduate students in the field of artificial intelligence, robotics and information technology. It is will also appeal to a wide range of readers interested in expanding the functionality of artificial intelligence systems. One of the pressing problems of modern artificial intelligence systems is the development of integrated hybrid systems based on deep learning. Unfortunately, there is currently no universal methodology for developing topologies of hybrid neural networks (HNN) using deep learning. The development of such systems calls for the expansion of the use of neural networks (NS) for solving recognition, classification and optimization problems. As such, it is necessary to create a unified methodology for constructing HNN with a selection of models of artificial neurons that make up HNN, gradually increasing the complexity of their structure using hybrid learning algorithms.