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Biomimetic Characteristics of an Active Deployable Structure

Related publications (32)

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Multiclass Transfer Learning from Unconstrained Priors

Barbara Caputo, Jie Luo, Tatiana Tommasi

The vast majority of transfer learning methods proposed in the visual recognition domain over the last years ad- dresses the problem of object category detection, assuming a strong control over the priors from which transfer is done. This is a strict condi ...

2011

Multiclass Transfer Learning from Unconstrained Priors

Barbara Caputo, Jie Luo, Tatiana Tommasi

Idiap2011

Robust Bayesian reinforcement learning through tight lower bounds

Christos Dimitrakakis

In the Bayesian approach to sequential decision making, exact calculation of the (subjective) utility is intractable. This extends to most special cases of interest, such as reinforcement learning problems. While utility bounds are known to exist for this ...

2011

Learning and Control of UAV maneuvers Based on Demonstrations

Aude Billard, Seyed Mohammad Khansari Zadeh

Many maneuvers of Unmanned Aerial Vehicles (UAV) can be considered within a framework of trajectory following. Though this issue can differ from one application to another, they all share the same problem of finding an optimal path (or signal) to perform t ...

2009

On-line learning and modulation of periodic movements with nonlinear dynamical systems

Auke Ijspeert

Abstract The paper presents a two-layered system for (1) learning and encoding a periodic signal without any knowledge on its frequency and waveform, and (2) modulating the learned periodic trajectory in response to external events. The system is used to l ...

2009

Adaptive civil engineering structures

Bernard Adam

Most civil structures are passive and static. They are designed according to serviceability and safety requirements. When subjected to actions, they generally deflect in a passive manner. For example, they do not adapt actively to external loading. A more ...

EPFL2007

Effects of stress and genotype on meta-parameter dynamics in reinforcement learning

Maria del Carmen Sandi Perez, Wulfram Gerstner, Gediminas Luksys, Jérémie Knüsel

Stress and genetic background regulate different aspects of behavioral learning through the action of stress hormones and neuromodulators. In reinforcement learning (RL) models, meta-parameters such as learning rate, future reward discount factor, and expl ...

2007

Alexandre Sarrasin (1895-1976) et l'esthétique de l'ingénieur

Philippe Mivelaz

Alexandre Sarrasin (1895-1976) studied at Zürich Federal Swiss Institute of Technology (ETH) from 1913 to 1918. Despite First World War's conflicts surrounding the neutral Switzerland, the intellectual climate inside ETH was cosmopolitan and liberal. As un ...

EPFL2007

Behaviour design in microrobots

Masoud Asadpour

In order to verify models of collective behaviors of animals, robots could be manipulated to implement the model and interact with real animals in a mixed-society. This thesis describes design of the behavioral hierarchy of a miniature robot, that is able ...

EPFL2006

EDITORIAL: Robot Programming By Demonstration

Aude Billard, Roland Siegwart

Programming by demonstration (PbD) is a key research topic in robotics. It impacts both fundamental research and application-oriented studies.Work in that area tackles the development of robust algorithms for motor control, motor learning, gesture recognit ...

2004