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Editorial
Special issue: HAIS 2010
The language of logic has been the basic tool for the development of science and technology through rigorous reasoning. It was the paradigm of science until the famous Incompleteness Theorem of Kurt G¨odel set its limits, closing an epoch of orthodox thinking that opened science to new avenues of modelling reality. The incompleteness of logic paved the way to statistics as the main tool to describe our world. The language of logic was also the mainstream of Artificial Intelligence during a long period of its establishment as a discipline, and it did also come to its limits in this field. The result of this change in paradigm in Artificial Intelligence was the emergence of hybrid languages, such as the fuzzy reasoning-based systems, and computational models, such as the ones inspired in biology:
artificial neural networks, evolutionary algorithms. Statistics and graph theory have met in the fields of Bayesian reasoning for knowledge representation, and ontology-based data mining. The new paradigm of Artificial Intelligence is the design of system based on the combination of apparently diverse computational and modelling approaches, searching for the appropriate fit to the desired functionality. Intelligent systems are pervasive in our society and growing in size and complexity at an astonishing pace, and the response to the coming challenges will come, as always has, from the hand of hierarchical thinking, modularity and the ability to decompose problems and find the best partial solution. In this paradigm, Hybrid Intelligent Systems are the natural approach to the problems, rather than the exceptional case.
This special issue comprising of 10 papers is focused on different hybrid learning approaches and its real-world applications. They are a collection of extended papers presented at the 5th International Conference on Hybrid Artificial Intelligence Systems held in San Sebasti´an, Spain, in June of 2010, and organized by the Computational Intelligence Group (GIC) of the University of the Basque Country.
Papers were selected on the basis of fundamental ideas/concepts rather than the direct usage of well-established techniques. This issue is then aimed at practitioners, researchers and postgraduate students who are engaged in developing and applying advanced intelligent systems principles to solving real-world problems. The papers are organized as follows.
In the first contribution by Gallegoet al. [4], they propose a Morphological Cellular Automata (MCA) with assured convergence to a state characterized by morphological dependences and inde- pendences between neighbouring cell states for image segmentation. The resulting configuration of cell states is composed of homogeneous regions whose boundaries are defined by the morphological independence relation.
Pinteaet al. [8] describe a hybrid ant-based approach to the well-known bandwidth minimization problem. Two local search procedures are specifically designed to reduce the bandwidth and used for solution improvement within various ant colony system algorithms. Computational experiments show a good performance of the new hybrid methods for several bandwidth minimization problem instances.
The article by Zatoet al. [10] describes a system based on virtual organizations of agents that allows recommendations about planning of tasks to minimize the resources necessary for their accomplishment and to obtain the maximum profit. For this purpose, a hybrid artificial intelligence system with genetic algorithm, queuing theory and CBR is used to obtain an efficient distribution.
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534 Editorial
The work by Caseset al. [3] deals with modelling the emergence of pathological crowd behaviours (avalanches and stranding) in the event of emergency evacuations. A hybrid model fusing spatial, social and logical models is able to reproduce such behaviours, as verified by a large number of simulations. Furthermore, we have identified the type of logic associated with each of the pathological behaviour: Boolean logic reasoning model produce avalanches. Diamond logic reasoning model produce stranded crowds.
To handle imprecision and incomparability in decision making applications, the paper by Heet al.
[5] investigates resolution-based automated reasoning within an established finite lattice-valued logic system. The strategy and algorithm for testing the satisfiability of formulae and the lock-resolution automated reasoning algorithm are proposed, respectively
The objective of the article by Bankovi´cet al. [1] is to provide an efficient hand gesture recog- nition suitable for the implementation in devices with limited resources, such as cameras. The pro- posed model of the gestures captures their temporal properties, which significantly reduces storage requirements, and avoids segmentation process. The gestures are further classified using clustering techniques. The main advantage of the approach is its simplicity, which enables the implementation using devices with limited resources, and therefore low cost.
The work by Simi´cet al. [9] focuses on multivariate discriminant analysis and self-organized maps are used to create an insolvency prediction model that could effectively predict any future failure of a finance company.
Calvo and Corchado [2] present a novel bio-inspired knowledge method, based on gain scheduling, for the calculation of a proportional–integral–derivative controller (PID controller) parameters that will prevent system instability. The aim is to prevent a transition to control system instability due to undesirable controller parameters that may be introduced manually by an operator.
The contribution by Kudelkaet al. [6] introduces a social network analysis based on the so-called Forgetting Curve and Swarm Intelligence inspired by the Ant Colony Optimization. They analyse a co-authorship network and identify two types of ties among its nodes. The Forgetting Curve and Swarm Intelligence are used to model the dynamics of such a network.
In the end, Kurlej and Wozniak [7] focus on the problem of the concept drift using active learning approach for the minimal distance classifiers. The potential for adaptation of the proposed method and its quality are evaluated through computer experiments, carried out on several benchmark data sets.
References
[1] Z. Bankovi´c, J. M. Moya, E. Romero, J. Blesa, D. Fraga, J. C. Vallejo, ´A. Araujo, P. Malag´on, J.-M. de Goyeneche, D. Villanueva, and O. Nieto-Taladriz. Using clustering techniques for intelligent camera-based user interfaces. Logic Journal of the IGPL, 2011, doi:10.1093/jigpal/jzr008.
[2] J. L. Calvo-Rolle and E. Corchado. A bio-inspired robust controller for a refinery plant process.
Logic Journal of the IGPL, 2011, doi:10.1093/jigpal/jzr010.
[3] B. Cases, I. Rebollo, and M. Gra˜na. A spatial-social-logical model explaining human behavior in emergency situations.Logic Journal of the IGPL, 2011, doi:10.1093/jigpal/jzr006.
[4] J. Gallego, C. Hernandez, and M. Gra˜na. A morphological cellular automata based on morphological independence.Logic Journal of the IGPL, 2011 doi:10.1093/jigpal/jzr003.
[5] X. He, J. Liu, Y. Xu, L. Martínez, and D. Ruan. On α-satisfiability and its α-lock resolu- tion in a finite lattice-valued propositional logic LnP(X). Logic Journal of the IGPL, 2011, doi:10.1093/jigpal/jzr007.
[14:35 3/5/2012 jzr001.tex] Paper Size: a4 paper Job: JIGPAL Page: 535 533–535
Editorial 535 [6] M. Kudelka, Z. Hor´ak, V. Sn´asel, P. Kromer, J. Platos, and A. Abraham. Social and swarm aspects of co-authorship network.Logic Journal of the IGPL, 2011, doi:10.1093/jigpal/jzr002.
[7] B. Kurlej and M. Wozniak. Active learning approach to concept drift problem.Logic Journal of the IGPL, 2011, doi:10.1093/jigpal/jzr011.
[8] C.-M. Pintea, G. C. Crisan, and C. Chira. Hybrid ant models with a transition policy for solving a complex problem.Logic Journal of the IGPL, 2011, doi:10.1093/jigpal/jzr004.
[9] D. Simi´c, I. Kovaˇcevi´c, and S. Simi´c. Insolvency prediction for assessing corporate financial health.Logic Journal of the IGPL, 2011, doi:10.1093/jigpal/jzr009.
[10] C. Zato, A. de Luis, J. Bajo, J. F. De Paz, and J. M. Corchado. Dynamic model of distribu- tion and organization of activities in multi-agent systems.Logic Journal of the IGPL, 2011, doi:10.1093/jigpal/jzr005.
Manuel Gra ˜na Computational Intelligence Group, Department of Computer Science and Artificial Intelligence, The University of the Basque Country, San Sebastian, Spain e-mail: [email protected] Emilio Corchado Departamento de Inform´atica y Autom´atica, University of Salamanca, Plaza de la Merced S/N, 37008, Salamanca, Spain e-mail: [email protected] Michal Wozniak Department of Systems and Computer Networks, Faculty of Electronics, Wroclaw University of Technology, Wybrzeze Wyspianskiego 27, 50-370, Wroclaw, Poland e-mail: [email protected]
