Neuroevolution and complexifying genetic architectures for memory and control tasks

The way genes are interpreted biases an artificial evolutionary system towards some phenotypes. When evolving artificial neural networks, methods using direct encoding have genes representing neurons and synapses, while methods employing artificial ontogeny interpret genomes as recipes for the construction of phenotypes. Here, a neuroevolution system (neuroevolution with ontogeny or NEON) is presented that can emulate a well-known neuroevolution method using direct encoding (neuroevolution of augmenting topologies or NEAT), and therefore, can solve the same kinds of tasks. Performance on challenging control and memory benchmark tasks is reported. However, the encoding used by NEON is indirect, and it is shown how characteristics of artificial ontogeny can be introduced incrementally in different phases of evolutionary search

Micro-timing of backchannels in human-robot interaction

Inden B, Malisz Z, Wagner P, Wachsmuth I. Micro-timing of backchannels in human-robot interaction. Presented at the Timing in Human-Robot Interaction: Workshop in Conjunction with the 9th ACM/IEEE International Conference on Human-Robot Interaction (HRI2014), Bielefeld, Germany

'Ja, mhm, ich verstehe dich' - Oszillator-basiertes Timing multimodaler Feedback-Signale in spontanen Dialogen

Wagner P, Inden B, Malisz Z, Wachsmuth I. 'Ja, mhm, ich verstehe dich' - Oszillator-basiertes Timing multimodaler Feedback-Signale in spontanen Dialogen. In: Wolff M, ed. Elektronische Sprachsignalverarbeitung 2012 (Tagungsband ESSV) --- Studientexte zur Sprachkommunikation. Vol 64. Dresden: TUD Press; 2012: 179-187

Barbarians at the British Museum: Anglo-Saxon Art, Race and Religion

A critical historiographical overview of art historical approaches to early medieval material culture, with a focus on the British Museum collections and their connections to religion

Open-ended Coevolution and the Emergence of Complex Irreducible Functional Units in Iterated Number Sequence Games

Inden B. Open-ended Coevolution and the Emergence of Complex Irreducible Functional Units in Iterated Number Sequence Games. In: Proceedings of the 14th annual conference on genetic and evolutionary computation. New York, NY, USA: ACM; 2012: 113-200

Benchmarking Memory Evolution in Artificial Neural Networks

Inden B. Benchmarking Memory Evolution in Artificial Neural Networks. In: Jost J, ed. Proceedings of the European Conference on Complex Systems. 2007

Supplemental files for article: Machine learning of symbolic compositional rules with genetic programming: Dissonance treatment in Palestrina

Supplemental files for the article: Machine learning of symbolic compositional rules with genetic programming: Dissonance treatment in Palestrina, to be submitted. Contains Python scripts and output data. Please see _Readme.txt in every directory for more information

Rapid entrainment to spontaneous speech: A comparison of oscillator models

Oscillator models may be used for modeling synchrony between gestures and speech, or timing of backchanneling and turn-taking in dialogues. We find support for the hypothesis that oscillator networks can better predict rhythmic events on the syllable and foot level than single oscillators, but we do not find support for the hypothesis that phase resetting oscillators perform better that phase adapting oscillators. Overall, oscillators can be used to predict rhythmic events in speech, but higher level information needs to be integrated into such models to reach a satisfactory performance

Evolving neural fields for problems with large input and output spaces

Inden B, Jin Y, Haschke R, Ritter H. Evolving neural fields for problems with large input and output spaces. Neural Networks. 2012;28:24-39