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Meta Morphic Particle Swarm Optimization

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Distributed Scalable Multi-Robot Learning using Particle Swarm Optimization

Alcherio Martinoli, James Pugh

Designing effective behavioral controllers for mobile robots can be difficult and tedious; this process can be circumvented by using online learning techniques which allow robots to generate their own controllers online in an automated fash- ion. In multi- ...

2009

Distributed Adaptation in Multi-Robot Search using Particle Swarm Optimization

Alcherio Martinoli, James Pugh

We present an adaptive strategy for a group of robots engaged in the localization of multiple targets. The robotic search algorithm is inspired by chemotaxis behavior in bacteria, and the algorithmic parameters are updated using a distributed implementatio ...

2008

Multiple Heterogeneous Ant Colonies with Information Exchange

Arash Arami, Bijan Rahimzadeh Rofoee

The method of multiple heterogeneous ant colonies with information exchange (MHACIE) is presented in this paper with emphasis on the speed of finding the optimal solution and the corresponding computational complexity. The proposed method which is inspired ...

2008

Convolution Operators And Homomorphisms Of Locally Compact Groups

Let 1 < p < infinity, let G and H be locally compact groups and let c) be a continuous homomorphism of G into H. We prove, if G is amenable, the existence of a linear contraction of the Banach algebra CVp (G) of the p-convolution operators on G into CVp (H ...

Cambridge University Press2008

Inspiring and Modeling Multi-Robot Search with Particle Swarm Optimization

Alcherio Martinoli, James Pugh

Within the field of multi-robot systems, multi-robot search is one area which is currently receiving a lot of research attention. One major challenge within this area is to design effective algorithms that allow a team of robots to work together to find th ...

2007

Discrete Multi-Valued Particle Swarm Optimization

Alcherio Martinoli, James Pugh

Discrete optimization is a difficult task common to many different areas in modern research. This type of optimization refers to problems where solution elements can assume one of several discrete values. The most basic form of discrete optimization is bin ...

2006

Applying Aspects of Multi-Robot Search to Particle Swarm Optimization

Alcherio Martinoli, James Pugh, Loïc Segapelli

We present a modified version of the Particle swarm Optimization algorithm in which we adjust the virtual swarm search by incorporating inter-agent dynamics native to multi-robot search scenarios. The neighborhood structure of PSO is modified to accurately ...

2006

On Interpolation and Resampling of Discrete Data

Pouya Dehghani Tafti

This letter introduces a new representation of discrete signals based on the mathematical notions of functionals and continuous dual spaces. A new and more general sampling theorem is also suggested. Next, the problems of interpolating and resampling discr ...

IEEE2006

Particle swarm optimization for unsupervised robotic learning

Alcherio Martinoli, James Pugh

We explore using particle swarm optimization on problems with noisy performance evaluation, focusing on unsupervised robotic learning. We adapt a technique of overcoming noise used in genetic algorithms for use with particle swarm optimization, and evaluat ...

2005

Co-Evolutionary Particle Swarm Optimization Applied to the 7x7 Seega Game

Sara Mitri

Seega is an ancient Egyptian two-stage board game that, in certain aspects, is more difﬁcult than chess. The two-player game is most commonly played on a 7 × 7 board, but is also sometimes played on a 5 × 5 or 9 × 9 board. In the ﬁrst and more difﬁcult sta ...

2004