Header logo is al


7 results (BibTeX)

2016


no image
Extrapolation and learning equations

Martius, G., Lampert, C. H.

2016, arXiv preprint \url{https://arxiv.org/abs/1610.02995} (misc)

[BibTex]

2016

[BibTex]


no image
Dynamical self-consistency leads to behavioral development and emergent social interactions in robots.

Der, R., Martius, G.

In Proc. IEEE Int. Conf. on Development and Learning and Epigenetic Robotics, 2016, in press (inproceedings)

[BibTex]

[BibTex]


no image
Compliant control for soft robots: emergent behavior of a tendon driven anthropomorphic arm.

Martius, G., Hostettler, R., Knoll, A., Der, R.

In 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pages: 767-773, 2016 (inproceedings)

DOI [BibTex]

DOI [BibTex]

2013


no image
Linear combination of one-step predictive information with an external reward in an episodic policy gradient setting: a critical analysis

Zahedi, K., Martius, G., Ay, N.

Frontiers in Psychology, 4(801), 2013 (article)

Abstract
One of the main challenges in the field of embodied artificial intelligence is the open-ended autonomous learning of complex behaviours. Our approach is to use task-independent, information-driven intrinsic motivation(s) to support task-dependent learning. The work presented here is a preliminary step in which we investigate the predictive information (the mutual information of the past and future of the sensor stream) as an intrinsic drive, ideally supporting any kind of task acquisition. Previous experiments have shown that the predictive information (PI) is a good candidate to support autonomous, open-ended learning of complex behaviours, because a maximisation of the PI corresponds to an exploration of morphology- and environment-dependent behavioural regularities. The idea is that these regularities can then be exploited in order to solve any given task. Three different experiments are presented and their results lead to the conclusion that the linear combination of the one-step PI with an external reward function is not generally recommended in an episodic policy gradient setting. Only for hard tasks a great speed-up can be achieved at the cost of an asymptotic performance lost.

link (url) DOI [BibTex]


no image
Behavior as broken symmetry in embodied self-organizing robots

Der, R., Martius, G.

In Advances in Artificial Life, ECAL 2013, pages: 601-608, MIT Press, 2013 (incollection)

[BibTex]

[BibTex]


no image
Information Driven Self-Organization of Complex Robotic Behaviors

Martius, G., Der, R., Ay, N.

PLoS ONE, 8(5):e63400, Public Library of Science, 2013 (article)

link (url) DOI [BibTex]

link (url) DOI [BibTex]


no image
Robustness of guided self-organization against sensorimotor disruptions

Martius, G.

Advances in Complex Systems, 16(02n03):1350001, 2013 (article)

Abstract
Self-organizing processes are crucial for the development of living beings. Practical applications in robots may benefit from the self-organization of behavior, e.g.~to increase fault tolerance and enhance flexibility, provided that external goals can also be achieved. We present results on the guidance of self-organizing control by visual target stimuli and show a remarkable robustness to sensorimotor disruptions. In a proof of concept study an autonomous wheeled robot is learning an object finding and ball-pushing task from scratch within a few minutes in continuous domains. The robustness is demonstrated by the rapid recovery of the performance after severe changes of the sensor configuration.

DOI [BibTex]

DOI [BibTex]