Benjamin Dittes, Alexander Gepperth, Antonello Ceravola, Jannik Fritsch, Christian Goerick,
"Self-management for neural dynamics in brain-like information processing",
Proceedings of the 6th International Conference on Autonomic Computing and Communications, 2009.
Abstract
Neural dynamics coupled by adaptive synaptic information transmission provide a very powerful tool for biologically inspired visual processing systems[4]. Currently, progress is limited by the computing time needed to evaluate the underlying equations and by the high number of parameters necessary to tune to achieve the desired system performance. In this contribution we apply Autonomic Computing techniques to overcome these limitations. We appro...
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Miguel Vaz,
"Developmentally inspired computational framework for embodied speech imitation",
Universidade do Minho, Escola de Engenharia, 2009.
Abstract
This thesis is concerned with the autonomous acquisition of speech production skills by a robotic system. The acquisition should occur in interaction with a human tutor, making little or no assumptions on the vocabulary and language of interaction. A particular target embodiment of the acquisition framework presented in this thesis is the humanoid robot Asimo. Because of its size, and the little knowledge of the world it possesses, a child’s vo...
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Yaochu Jin, Robin Gruna, Bernhard Sendhoff,
"Pareto Analysis of Evolutionary and Learning Systems",
Frontiers of Computer Science in China, vol. 3, no. 1, pp. 4–17, 2009.
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Martin Heracles, Bram Bolder, Christian Goerick,
"Fast Detection of Arbitrary Planar Surfaces from Unreliable 3D Data",
International Conference on Intelligent Robots and Systems (IROS), 2009.
Abstract
Man-made real-world environments are dominated by planar surfaces many of which constitute behaviorrelevant entities. Thus, the ability to perceive planar surfaces is vital for any embodied system operating in such environments, be it human or robotic. In this paper, we present an architecture for detection and estimation of planar surfaces in the scene from calibrated stereo images. They are represented in a behavior-oriented way, focusing on ge...
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Katrin Lohan, Anna-Lisa Vollmer, Jannik Fritsch, Katharina Rohlfing, Britta Wrede,
"Which ostensive stimuli can be used for a robot to detect and maintain tutoring situations?",
Int. Workshop on Social Signals Processing, 2009.
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Matthew Howard, Stefan Klanke, Michael Gienger, Christian Goerick, Sethu Vijayakumar,
"A Novel Method for Learning Policies from Variable Constraint Data",
Autonomous Robots, 2009.
Abstract
Many everyday human skills can be framed in terms of performing some task subject to constraints imposed by the environment.Constraints are usually unobservable and frequently change between contexts. In this paper, we present a novel approach for learning (unconstrained) control policies from movement data, where observations come from movements under different constraints. As a key ingredient, we introduce a small but highly effective modificat...
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Michael Ortiz and Alexander Gepperth,
"Local self-adaptation mechanisms for large-scale neural system building",
Proceedings of the 2nd International Conference on Cognitive Neurodynamics, 2009.
Abstract
For integrating neural networks into large systems, dynamical stability and parameter settings are key issues, especially for popular recurrent network models such as dynamic neural fields. In neural circuits, homeostatic plasticity seems to counter these problems. Here we present a set of gradient adaptation rules that autonomously regulate the strength of synaptic input and the parameters of the transfer function for each neuron individually. B...
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Stephan Kirstein, Alexander Denecke, Stephan Hasler, Heiko Wersing, Horst-Michael Groß, Edgar Körner,
"A Vision Architecture for Unconstrained and Incremental Learning of Multiple Categories",
Memetic Computing, vol. 1, no. 4, pp. 291–304, 2009.
Abstract
We present an integrated vision architecture capable of incrementally learning several visual categories based on natural hand-held objects. Ad- ditionally we focus on interactive learning, which requires real-time image processing methods and a fast learning algorithm. The overall system is composed of a figure-ground segregation part, several feature extraction methods and a life-long learning approach combining incremental learn- ing with cate...
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Yaochu Jin, Yan Meng, Bernhard Sendhoff,
"Evolvability and robustness of in silico evolution of gene regulatory dynamics",
Foundations of Systems Biology in Engineering, pp. 68–71, 2009.
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Soundappan Ramanathan,
"Knowledge Incorporation into Evolutionary Algorithms to Speed up Aerodynamic Design Optimization",
University of Stuttgart, 2009.
Abstract
This work deals with making the search process with Evolution Strat- egy with Covariance Matrix Adaptation (CMA-ES) more efficient. Methods are proposed to initialise the optimisation with predefined knowledge instead using a random initialisation in the context of aero- dynamic design optimisation. In aerodynamics, the search for better shape is always in research. Conventional numerical optimisation pro- cesses results in huge amount of data se...
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