Combinations of Intelligent Methods and Applications

This volume includes extended and revised versions of the papers presented at the 4th Workshop on Combinations of Intelligent Methods and Applications (CIMA 2014) which was intended to become a forum for exchanging experience and ideas among researchers and practitioners dealing with combinations of different intelligent methods in Artificial Intelligence. The aim is to create integrated or hybrid methods that benefit from each of their components. Some of the existing presented efforts combine soft computing methods (fuzzy logic, neural networks and genetic algorithms). Another stream of efforts integrates case-based reasoning or machine learning with soft-computing methods. Some of the combinations have been more widely explored, like neuro-symbolic methods, neuro-fuzzy methods and methods combining rule-based and case-based reasoning. CIMA 2014 was held in conjunction with the 26th IEEE International Conference on Tools with Artificial Intelligence (ICTAI2014).

Presents combinations of intelligent methods and applications Details approaches covering different intelligent methods and technologies, such as argumentation methods, linear optimization methods, agents, probabilistic planning, ant-based algorithms, uncertainty methods, data visualization techniques, logics, hybrid logics, and evolutionary search Complete results of the 4th International Workshop, CIMA 2014, held at Limassol, Cyprus, November 2014 Includes supplementary material: sn.pub/extras

Inhalt
Evolutionary Landscape and Management of Population Diversity.- Probabilistic Planning in AgentSpeak Using the POMDP -Framework.- Ant-Based System Analysis on the Traveling Salesman Problem Under Real_World Settings.- Verifying Compliance for Business Process Logs with a Hybrid Logic Model Checker.- Smarter Electricity and Argumentation Theory.- Online Argumentation-based Platform for Recommending Medical Literature.- Medical Image Processing: A brief Survey and a New Theoretical Hybrid ACO Model.- Smoke Detection in Environmental Regions by Means of Computer Vision.