Michael Ortiz, Jannik Fritsch, Benjamin Dittes, Alexander Gepperth,
"Autonomous generation of internal representations for associative learning",
Artificial Neural Networks - ICANN 2010, Springer, 2010.
Abstract
In this contribution, we explore the possibilities of learning in large-scale, multimodal processing systems operating under real-world conditions. Using an instance of a large-scale object detection system for complex traffic scenes, we demonstrate that there is a great deal of very robust correlations between high-level processing results quantities, and that such correlations can be autonomously detected and exploited to improve performance. W...
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Claudius Gläser and Frank Joublin,
"An Adaptive Normalized Gaussian Network and Its Application to Online Category Learning",
Proceedings of the International Joint Conference on Neural Networks (IJCNN), IEEE World Congress on Computational Intelligence (WCCI), pp. 675–682, 2010.
Abstract
In online applications, where training samples sequentially arise during execution, incremental learning schemes have to be applied. In this paper we propose an adaptive Normalized Gaussian Network model (NGnet) suitable for incremental learning. Following a statistical account we present a truly sequential training procedure. Key to the learning algorithm are local unit manipulation mechanisms for network growth and pruning which continuously ad...
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Mathias Rudolph,
"Representing Feature Changes Caused by Actions",
HTW Dresden, 2010.
Abstract
In Programming by Demonstration, to solve complex tasks, a robot needs the ability to split a task into subgoals and find actions that will fulfill these subgoals. This is called planning. To be able to plan, the actions need to be stored in an inferable way. A simple generalizable method to store actions and their results is therefore one step into the direction of giving a robot the ability to solve complex tasks. This thesis proposes an approa...
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Till Steiner,
"Artificial Evolutionary Development",
Bielefeld University, 2010.
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Fernando Martinelli,
"Scene Layout Segmentation of Traffic Environments Using a Conditional Random Field",
University of Girona, 2010.
Abstract
At least 80% of the traffic accidents in the world are caused by human mistakes. Whether drivers are too tired, drunk or speeding, most accidents have their root in the improper behavior of drivers. Many of these accidents could be avoided if cars were equipped with some kind of intelligent system able to detect inappropriate actions of the driver and autonomously intervene by controlling the car in emergency situations. Such an advanced driver a...
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Benjamin Dittes and Christian Goerick,
"Unsupervised Self-Development in a Multi-Reward Environment",
Proceedings of the 10th International Workshop on Epigenetic Robotics, 2010.
Abstract
Self-development is an important quality for artificial agents, allowing skill development or improvement. In this contribution we analyze this problem for a scenario with multiple rewards, some easier to reach than others. There is no provided sequence of tasks to enforce self-development; rather, the agent must have an intrinsic motivation to discover more difficult reward sources even if a trivial one is always at hand. Then, by removing simpl...
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Lisa Schramm, Vander Martins, Yaochu Jin, Bernhard Sendhoff,
"Analysis of Gene Regulatory Network Motifs in Evolutionary Development of Multicellular Organisms",
Twelfth International Conference on the Synthesis and Simulation of Living Systems, 2010.
Abstract
Biological development is governed by gene regulatory networks (GRNs), although detailed genetic and cellular mechanisms underlying biological development remain unclear. It is believed that some GRN motifs have played an important role in the evolution of biological development by means of analyzing biological data. In this work, we investigate in a computational model for development to verify if these motifs can also be evolved as in biology, ...
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Claudius Gläser and Frank Joublin,
"Perceptually Grounded Word Meaning Acquisition: A Computational Model",
Proceedings of the Annual Meeting of the Cognitive Science Society (CogSci), pp. 1744–1749, 2010.
Abstract
We present a computational model for the incremental acquisition of word meanings. Inspired by Complementary Learning Systems theory the model comprises different components which are specifically tailored to satisfy the contradictory needs of (1) rapid memorization of word-scene associations and (2) statistical feature extraction to reveal word meanings. Both components are recurrently coupled to achieve a memory consolidation. This process refl...
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Nicole Naue, Daniel Strüber, Ingo Fründ, Jeanette Schadow, Daniel Lenz, Stefan Rach, Ursula Körner, Christoph Herrmann,
"Pattern reversal elicits stronger evoked and induced gamma-band responses than motion",
NeuroImage, vol. 55, no. 2, pp. 808-817, 2010.
Abstract
Hitherto, it is unclear whether gamma-band responses (GBRs, ≈40 Hz) of the electroencephalogram are more strongly modulated by visual stimulation with moving or rather with static objects. Most results suggest that GBRs occur more consistently in response to motion. We measured the electroencephalogram of healthy subjects watching high contrast, achromatic gratings. Briefly after their onset, the gratings either started to move or reversed thei...
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Gervasio Puertas, Jörg Bornschein, Marc Henniges, Jörg Lücke,
"The Maximal Causes of Natural Scenes are Edge Filters",
Advances in Neural Information Processing Systems, vol. 23, pp. 1939-1947, 2010.
Abstract
We study the application of a strongly non-linear generative model to image patches. As in standard approaches such as Sparse Coding or Independent Component Analysis, the mod
el assumes a sparse prior with independent hidden variables. However, in the place where standard approaches use the sum to combine basis functions we use the maximum. To derive tractable approximations for parameter estimation we apply a novel approach based on variationa...
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