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Activity Recognition Using Hybrid Generative/Discriminative Models on Home Environments Using Binary Sensors
TLDR
We describe the use of two powerful machine learning schemes, ANN (Artificial Neural Network) and SVM (Support Vector Machines), within the framework of HMM (Hidden Markov Model) in order to tackle the task of activity recognition in a home setting. Expand
Generating ensembles of heterogeneous classifiers using Stacked Generalization
TLDR
In this paper, we describe Stacking and its variants and present several examples of application domains. Expand
Controller for TORCS created by imitation
TLDR
This paper is an initial approach to create a controller for the game TORCS by learning how another controller or humans play the game. Expand
Time series forecasting by evolving artificial neural networks with genetic algorithms, differential evolution and estimation of distribution algorithm
TLDR
This paper evaluates three methods to evolve neural networks architectures, one carried out with genetic algorithm, a second one carriedout with differential evolution algorithm (DE) and the last one using estimation of distribution algorithms (EDA). Expand
A human-like TORCS controller for the Simulated Car Racing Championship
TLDR
This paper presents a controller for the 2010 Simulated Car Racing Championship. Expand
Web news mining in an evolving framework
TLDR
We present an approach for classifying in real-time web news articles into various categories (topic areas) based on the text content of the articles. Expand
GA-stacking: Evolutionary stacked generalization
TLDR
Stacking is a widely used technique for combining classifiers and improving prediction accuracy. Expand
Genetic Approach for Optimizing Ensembles of Classifiers
TLDR
An ensemble of classifiers is a set of classifier whose predictions are combined in some way to classify new instances. Expand
Neural networks robot controller trained with evolution strategies
TLDR
Neural networks (NN) can be used as controllers in autonomous robots. Expand
A Machine Consciousness Approach to the Design of Human-Like Bots
TLDR
This chapter introduces Machine Consciousness as a new research field applied to the development of human-like behaviour of non-player characters (NPCs) in video games using the cognitive architecture CERA-CRANIUM as an illustrative example of an autonomous control system inspired by cognitive theories of human consciousness. Expand
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