Obtaining a bayesian network from data is a learning process that is divided in two steps: structural learning and parametric learning. In this paper, we define an automatic learni...
Believability of computerised agents is a growing area of research. This paper is focused on one aspect of believability - believable movements of avatars in normative 3D Virtual W...
Anton Bogdanovych, Simeon J. Simoff, Marc Esteva, ...
Sampling methods are a direct approach to tackle the problem of class imbalance. These methods sample a data set in order to alter the class distributions. Usually these methods ar...
Ronaldo C. Prati, Gustavo E. A. P. A. Batista, Mar...
This paper presents an approach for mining fuzzy Association Rules (ARs) relating the properties of composite items, i.e. items that each feature a number of values derived from a ...
Go is a strategic two player boardgame of Chinese origin. In terms of game theory, it is a deterministic perfect information game. But despite of these factors it is terribly comp...
Autonomous Intelligent Systems (AIS) integrate planning, learning, and execution in a closed loop, showing an autonomous intelligent behavior. A Learning Life Cycle (LLC) Operators...
Genetic programming is known to provide good solutions for many problems like the evolution of network protocols and distributed algorithms. In such cases it is most likely a hard...
Thomas Weise, Michael Zapf, Mohammad Ullah Khan, K...