The purpose of this paper is to introduce a multi-agent model for plan synthesis in which the production of a global shared plan is based on a promising unified framework based on...
Abstract. Long Short-Term Memory (LSTM) recurrent neural networks (RNNs) are local in space and time and closely related to a biological model of memory in the prefrontal cortex. N...
Many applications refer to moving objects or phenomena and require spatio-temporal modelling and specific analysis. Unlike conventional data where attributes are simple values (nu...
A central issue in relational learning is the choice of an appropriate bias for limiting first-order induction. The purpose of this study is to circumvent this issue within a unifo...
Abstract. A theoretical analysis for comparing two linear dimensionality reduction (LDR) techniques, namely Fisher's discriminant (FD) and Loog-Duin (LD) dimensionality reduci...