In machine learning theory, problem classes are distinguished because of di erences in complexity. In 6 , a stochastic model of learning from examples was introduced. This PAClear...
Abstract. In this paper, we propose a new strategic and tactic reasoning for agent communication. This reasoning framework is specified using argumentation theory combined to a rel...
Abstract. This paper provides a framework enabling to define and determine the complexity of various universal programs U for various machines. The approach consists of first defin...
The relative depth of objects causes small shifts in the left and right retinal positions of these objects, called binocular disparity. Here, we describe a neuromorphic implementa...
While quantitative probabilistic networks (QPNs) allow the expert to state influences between nodes in the network as influence signs, rather than conditional probabilities, infer...