Titlebook: Current Topics in Artificial Intelligence; 13th Conference of t Pedro Meseguer,Lawrence Mandow,Rafael M. Gasca Conference proceedings 2010

CESS

An Analysis of Particle Properties on a Multi-swarm PSO for Dynamic Optimization Problems helpful immediately after a change in the environment has occurred, while trajectory particles lead the optimization in the final stages. Suggestions on how to use this knowledge for future developments are also provided.

溫室

An Incremental Learning Method for Neural Networks Based on Sensitivity Analysise managed but the computing resources are limited. In this paper an incremental version of the SBLLM is presented. The theoretical basis for the method is given and its performance is illustrated by comparing the results obtained by the on-line and batch mode versions of the algorithm.

MORPH

CBR Outcome Evaluation for High Similar Cases: A Preliminary Approach very close. To this end, we propose three techniques to obtain a reliance solution degree, one based on case retrieval and two based on case adaptation. We also show the capacities of this proposal in a medical problem.

packet

On the Suitability of Combining Feature Selection and Resampling to Manage Data Complexityracks than melodic tracks, and where features were aggregated without any correlation study. Results showed that the most effective combination was the ordered use of resampling and feature reduction techniques.

其他

Developing Strategies for the ART Domainm since the agent has to decide when to interact with the known agents and when to look for new ones. The agent, called Uno2008, competed in and won the Third International ART Testbed Competition held at AAMAS in March 2008.

wreathe

空洞

Cpap155

Dendritic-Cells

Agrar- und Agrarstrukturpolitiknother one specialized in short words. To this end, various multilayer perceptrons have been trained to classify a subset of the vocabulary in a holistic manner. Combining the classifiers by means of a variation of the Borda count voting method achieves very satisfying results.

interpose

?sterreichische Privatrechtsgeschichteled data instances, from which constraints can be derived, ranks these instances on their usability and then derives constraints from the top-ranked instances only. Our experiments show that . chooses, respectively reduces, the set of candidate constraints without compromising the quality of the derived model.