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Analysis of Fitness Noise in Particle Swarm Optimization: From Robotic Learning to Benchmark Functions

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Real-Time Estimate of Velocity and Acceleration of Quasi-Periodic Signals Using Adaptive Oscillators

Auke Ijspeert, Renaud Ronsse

Estimation of the temporal derivatives of a noisy position signal is a ubiquitous problem in industrial and robotics engineering. Here, we propose a new approach to get velocity and acceleration estimates of cyclical/periodic signals near to steady-state r ...

Ieee-Inst Electrical Electronics Engineers Inc2013

Poisson Image Reconstruction With Hessian Schatten-Norm Regularization

Michaël Unser, Stamatios Lefkimmiatis

Poisson inverse problems arise in many modern imaging applications, including biomedical and astronomical ones. The main challenge is to obtain an estimate of the underlying image from a set of measurements degraded by a linear operator and further corrupt ...

Ieee-Inst Electrical Electronics Engineers Inc2013

From N to N+1: Multiclass Transfer Incremental Learning

Barbara Caputo, Ilja Kuzborskij

Since the seminal work of Thrun [16], the learning to learn paradigm has been defined as the ability of an agent to improve its performance at each task with experience, with the number of tasks. Within the object categorization domain, the visual learning ...

2013

Meta Morphic Particle Swarm Optimization

Auke Ijspeert, Soha Pouya, Jesse van den Kieboom

Particle Swarm Optimization is a simple and elegant optimization algorithm used to solve a large variety of different real-valued problems. When it comes to solving combinations of continuous and discrete problems however, PSO by itself is not very well su ...

Springer2013

Synergy-level Grasp Synthesis Learning

Aude Billard, Sahar El Khoury, Miao Li

Autonomous grasping is a complex task for robots. It is a high dimensional problem since it involves controlling for the hand position, orientation and joint angles to successfully grasp an object. In order to reduce the control complexity, we adopt a 3-st ...

2013

BI-population CMA-ES Algorithms with Surrogate Models and Line Searches

Ilya Loshchilov

In this paper, we study the performance of NIPOP-aCMA- ES and NBIPOP-aCMA-ES, recently proposed alternative restart strategies for CMA-ES. Both algorithms were tested using restarts till a total number of function evaluations of 106D was reached, where D i ...

2013

Bio-Inspired Decentralized Radio Access Based on Swarming Mechanisms Over Adaptive Networks

Ali H. Sayed

The goal of this paper is to study the learning abilities of adaptive networks in the context of cognitive radio networks and to investigate how well they assist in allocating power and communications resources in the frequency domain. The allocation mecha ...

Institute of Electrical and Electronics Engineers, Inc., 345 E. 47 th St. NY NY 10017-2394 United States2013

Distributed Particle Swarm Optimization for Limited Time Adaptation in Autonomous Robots

Alcherio Martinoli, Ezequiel Leonardo Di Mario

Evaluative techniques offer a tremendous potential for on-line controller design. However, when the optimization space is large and the performance metric is noisy, the time needed to properly evaluate candidate solutions becomes prohibitively large and, a ...

2012

Diffusion Adaptation Strategies for Distributed Optimization and Learning Over Networks

Ali H. Sayed

We propose an adaptive diffusion mechanism to optimize global cost functions in a distributed manner over a network of nodes. The cost function is assumed to consist of a collection of individual components. Diffusion adaptation allows the nodes to coopera ...

IEEE2012

Modelling and Optimizing the Process of Learning Mathematics

This paper introduces a computer-based training program for enhancing numerical cognition aimed at children with developmental dyscalculia. Through modelling cognitive processes and controlling the level of their stimulation, the system optimizes the learn ...

Springer2012