Multi Agent Based Simulation (MABS) has been used mostly in purely social contexts. However, compared to other approaches, e.g., traditional discrete event simulation, object-orien...
There is a growing belief that the agents' cognitive structures play a central role on the enhancement of predicative capacities of decision-making strategies. This paper anal...
Discovering and studying emergent phenomena are among the most important activities in social research. Replicating this phenomenon in "the lab" using simulation is an i...
The effects of distinct agent interaction and activation structures are compared and contrasted in several multi-agent models of social phenomena. Random graphs and lattices repre...
Network Control is currently carried out mainly by means of signalling protocols. Although these protocols are robust and facilitate standardisation, they present several drawback...
Abstract. An off-line hand-written Chinese character recognizer supporting a vocabulary of 4,616 Chinese characters, alphanumerics and punctuation symbols has been reported. Traine...
Observational learning algorithm is an ensemble algorithm where each network is initially trained with a bootstrapped data set and virtual data are generated from the ensemble for ...
Abstract. Ordinal data play an important part in financial forecasting. For example, advice from expert sources may take the form of "bullish", "bearish" or &qu...
Quantization of continuous variables is important in data analysis, especially for some model classes such as Bayesian networks and decision trees, which use discrete variables. Of...