By Rami N. Khushaba, Ahmed Al-Ani, Akram AlSukker, Adel Al-Jumaily (auth.), Marco Dorigo, Mauro Birattari, Christian Blum, Maurice Clerc, Thomas Stützle, Alan F. T. Winfield (eds.)
This booklet constitutes the refereed lawsuits of the sixth overseas Workshop on Ant Colony Optimization and Swarm Intelligence, ANTS 2008, held in Brussels, Belgium, in September 2008.
The 17 revised complete papers, 24 revised brief papers, and 10 prolonged abstracts offered have been rigorously reviewed and chosen from ninety one submissions. The papers conceal theoretical and foundational elements of computational intelligence and comparable disciplines with precise specialise in swarm intelligence and are dedicated to behavioral versions of social bugs and new algorithmic methods, empirical and theoretical examine in swarm intelligence, functions corresponding to ant colony optimization or particle swarm optimization, and theoretical and experimental study in swarm robotics systems.
Read or Download Ant Colony Optimization and Swarm Intelligence: 6th International Conference, ANTS 2008, Brussels, Belgium, September 22-24, 2008. Proceedings PDF
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Additional info for Ant Colony Optimization and Swarm Intelligence: 6th International Conference, ANTS 2008, Brussels, Belgium, September 22-24, 2008. Proceedings
The parameter α is ﬁxed at 1 and β is tested at 0, 1, and 2. When β equals 0, the expert knowledge weighting factor becomes 1 and does not aﬀect the updating of the pheromone, thus it is possible to examine the impact of expert knowledge on the ant colony optimization approach in this domain. 5.
For example, for n/pi = 3/7 the ratios were 88/10, 145/13, and 98/12 (see Table 2). Due to these facts, we set as a goal to obtain with the ACO algorithm, at least, a compound rule base with the same interpretability than the automated generated one. 1 Original Method Regarding the original ACO algorithm ‘AS’, it can be observed that, although it achieves rule bases with better interpretability than the initial set of single rules, it did not reach our goal of ﬁnding solutions, on average, as interpretable as the automatically generated rule bases in all the cases.
Blum, and G. Franc`es broadcasting. In this work we study this problem for two cases. In the ﬁrst one, each network node is equipped with an omni-directional antenna. However, omni-directional antennas often waste energy, for example, when information must only be sent to one neighboring node. Therefore, we also study the case of directional antennas, which additionally provide the advantage of reducing the interference with other nodes due to the reduced submission area. As most other works in this area we consider the following wireless communication model (see ).