We apply a constrained Hidden Markov Model architecture to the problem of simultaneous localization and surveying from sensor logs of mobile agents navigating in unknown environmen...
Abstract. Gaussian process models provide a probabilistic non-parametric modelling approach for black-box identification of nonlinear dynamic systems. The Gaussian processes can h...
Abstract. While there is strong motivation for using Gaussian Processes (GPs) due to their excellent performance in regression and classification problems, their computational com...
This paper takes an overtly anticipatory stance to the understanding of animat learning and behavior. It analyses four major animal learning theories and attempts to identify the a...
The central question in this paper is: Who (or what) constructs anticipations? I challenge the (tacit) assumption of Rosen’s standard definition of anticipatory systems according...
This is foremost a methodological contribution. It focuses on the foundation of anticipation and the pertinent implications that anticipation has on learning (theory and experiment...
Despite recent successes in control theoretical programs for limb control, behavior-based cognitive approaches for control are somewhat lacking behind. Insights in psychology and ...
Question classification is very important for question answering. This paper presents our research work on automatic question classification through machine learning approaches. W...