By Wenjun Zhang (editor)
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52 algorithm performance: i. To keep the population large enough, in order to avoid erratic behaviors. ii. To keep the effects on each kind of agent in equilibrium. The search should be neither excessively disperse nor be excessively concentrate. 5. ACE: Basic Framework + Population Dynamics This section is devoted to describe population dynamics. , and through the results of our previous experiments. 1. Schematic Description Threshold Response Functions The population dynamics follows the scheme as shown in figure 10.
2. ; 00 u The graphics show that the average entropy decreases when the number of foragers increases. This was also an expected result, because more patrollers mean more exploration· and thus higher levels of entropy. Obviously, the higher the ratio of foragers, the lower the level of entropy. lso when the population size increases. More agents means more patrollers which, in tum, means more exploratory searches. A low number of agents (approximately a population size below 20 agents) should be avoided because it may lead to erratic behaviors, due to the problem's degree of difficulty and the low number of available agents to solve it.
Lion. 0. 8 dyri • • • w • 'l o. 4. 8 dyn • • • 'ii ~ ~ 0. ~~~~~~~~~~~~~ 50 000 100 000 :;:: ~ 6:: · o. a l---~:;o~-l()Oci--~~o-1000 1500 500 No. Tours built ~ No. Tours built (e) Patrollers success probability evolution at early (f) Patrollers success probability complete evolution. jgure 22. Evolution of the pheromone table's average entropy (H~[i)), and evolution of the success probabilities for foragers and patrollers during an algorithm execution. The )~ft column shows these evolutions at early stages of the search, and the right column the 68 Jose B.