Transactions on Computational Collective Intelligence XVII

These transactions publish research in computer-based methods of computational collective intelligence (CCI) and their applications in a wide range of fields such as the semantic Web, social networks, and multi-agent systems. TCCI strives to cover new methodological, theoretical and practical aspects of CCI understood as the form of intelligence that emerges from the collaboration and competition of many individuals (artificial and/or natural). The application of multiple computational intelligence technologies, such as fuzzy systems, evolutionary computation, neural systems, consensus theory, etc., aims to support human and other collective intelligence and to create new forms of CCI in natural and/or artificial systems.

Inhalt

Multiagent Methodology to Reduce the Bullwhip Effect in a Supply Chain.- Behavioural Investigations of Financial Trading Agents using Exchange Portal.- An Overview of the Interrelation among Agent Systems, Learning Models and Formal Languages.- An Agent-Based Approach for Accident Analysis in Safety Critical Domains: A Case Study on a Runway Incursion Incident.- Inference of Markov chain models by using k-Testable Language: Application on aging people.- Finite Automata with Translucent Letters applied in Natural and Formal Language Theory.- Distributed Evacuation Route Planning Using Mobile Agents.- Situation Theory, Situated Information, and Situated Agents.- Conditional Preference Networks Support Multi-Issue Negotiations with Mediator.- Genetic Algorithm and Firefly Algorithm Hybrid Schemes for Cultivation Processes Modelling.- Color Quantization with Magnitude Sensitive Competitive Learning Algorithm.- A Subset-Based Ant Colony Optimisation with Tournament Path Selection for High-Dimensional Problems.- An Analysis of the Local Optima Storage Capacity of Hopfield Network Based Fitness Function Models.- On the Alzheimer's disease diagnosis: automatic spontaneous speech analysis.- Synthesis of Multicomponent Reuse Water Networks by PSO Approach.