Particle Swarm Optimization

Particle Swarm Optimization for container loading of nonorthogonal objects

Publication Type:

Conference Paper

Authors:

Isaac Cano; Vicenç Torra

Source:

ICAISC 2010, Springer, Volume 6114, Poland, p.403-410 (2010)

Learning from Sensors and Past Experience in an Autonomous Oceanographic Probe

Publication Type:

Conference Paper

Authors:

Albert Vilamala; Enric Plaza; Josep Lluis Arcos

Source:

Twenty-Second Conference on Innovative Applications of Artificial Intelligence Conference (IAAI-10), Association for the Advancement of Artificial Intelligence (AAAI), p.1859-1864 (2010)

Keywords:

PSO; Particle Swarm Optimization; CBR

Abstract:

The work presented in this paper is part of a multidisciplinary team collaborating in the deployment of an autonomous oceanographic probe with the task of exploring marine re- gions and take phytoplankton samples for their subsequent analysis in a laboratory. We will describe an autonomous system that, from sensor data, is able to characterize phyto- plankton structures. Because the system has to work inboard, a main goal of our approach is to dramatically reduce the di- mensionality of the problem. Specifically, our development uses two AI techniques, namely Particle Swarm Optimization and Case- Based Reasoning. We report results of experiments performed with simulated environments.

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