Abstract: A computer-based method for simulating a human-like decision in an environmental context, comprising: capturing environmental data with at least one sensor, realising a computer based method for realising a bi-directional compression of high dimensional data by compressing the data into a lower-dimensional map, if environmental data are captured during a learning phase of a computer-based model, evaluate the map of compressed data by determining the quality of the map by how well it separates data with different properties, the captured data corresponding to known pre-recorded data that have been pre-evaluated, if environmental data are captured after the learning phase, add new point to the compressed data and generate a signal indicating which human-like decision to use to correspond to the state of the operator.

Abstract: An apparatus for creating and training an artificial neural network (NN) performs iterations in which it implements and tests a version of a NN model, analyses the performance of the current NN model, generates a new NN module for improving the performance of the current NN model, adds the new NN module to the structure of the existing NN model to create a new NN model for executing, testing and analysing in the next iteration. In this way, the apparatus combines the creation and the testing of the NN model thereby improving the overall efficiency and the effectiveness of the development of NN based Al systems.

Abstract: A method for determining a driving intention of a user in a vehicle using electroencephalography (EEG) signals, comprising: acquiring (100) a plurality of EEG signals on a user in the vehicle, determining (101, . . . , 104) a plurality of features of the EEG signals, for each feature of the EEG signals, performing (111, . . . , 114?) a respective preliminary soft classification process, so as to obtain a plurality of preliminary soft predictions of driving intention each based on a feature of the EEG signals, performing (120) a soft classification process based on the plurality of preliminary soft predictions so as to obtain the driving intention of the user.

Abstract: A computer-based method for simulating a human-like decision in an environmental context, comprising: capturing environmental data with at least one sensor, realising a computer based method for realising a bi-directional compression of high dimensional data by compressing the data into a lower-dimensional map, if environmental data are captured during a learning phase of a computer-based model, evaluate the map of compressed data by determining the quality of the map by how well it separates data with different properties, the captured data corresponding to known pre-recorded data that have been pre-evaluated, if environmental data are captured after the learning phase, add new point to the compressed data and generate a signal indicating which human-like decision to use to correspond to the state of the operator.