Foraging bees use colour cues to help identify rewarding from unrewarding flowers, but as conditions change, bees may require behavioural flexibility to reverse their learnt preferences. Perceptually similar colours are learnt slowly by honeybees and thus potentially pose a difficult task to reverse-learn. Free-flying honeybees (N = 32) were trained to learn a fine colour discrimination task th...

Artificial bee colony (ABC), an optimization algorithm is a recent addition to the family of population based search algorithm. ABC has taken its inspiration from the collective intelligent foraging behavior of honey bees. In this study we have incorporated golden section search mechanism in the structure of basic ABC to improve the global convergence and prevent to stick on a local solution. T...

Swarm behavior is a relatively new technique in Artificial Intelligence with a wide variety of applications. Inspired by the social systems of colony insects such as ants and bees, swarm algorithms solve global problems through the local decisions and interactions of individual agents. In this project, swarm technology provides the distributed infrastructure used for resource discovery, area co...

In this paper, a mutation strategy that is based on Lévy Probabily Distribution is introduced in Artificial Bee Colony algorithm. The purpose is to better exploit promising solutions found by the bees. Such an approach is used to improve the performance of the original ABC in optimizing Least Squares Support Vector Machine hyper parameters. From the conducted experiment, the proposed lvABC show...

Honey bees (Apis mellifera) are increasingly in demand as pollinators for various key agricultural food crops, but globally honey bee populations are in decline, and honey bee colony failure rates have increased. This scenario highlights a need to understand the conditions in which colonies flourish and in which colonies fail. To aid this investigation we present a compartment model of bee popu...

The great majority of biological sequences share significant similarity with other sequences as a result of evolutionary processes, and identifying these sequence similarities is one of the most challenging problems in bioinformatics. In this paper, we present a discrete artificial bee colony (ABC) algorithm, which is inspired by the intelligent foraging behavior of real honey bees, for the det...

BACKGROUND Juvenile hormone (JH) plays an important role in honeybee development and the regulation of age-related division of labor. However, honeybees can be exposed to insect growth regulators (IGRs), such as JH analogs developed for insect pest and vector control. Although their side effects as endocrine disruptors on honeybee larval or adult stages have been studied, little is known about ...

This study was conducted to test for the effect of three stinging behaviors QTLs (sting-1, sting-2 and sting-3) on the expression of guarding and stinging behavior of individual honey bees, and to determine if results of defensive behavior QTLs found in studies with Africanized honey bees could be extended to other populations of bees. Samples of guards, stingers, foragers and nurse bees were t...

Glyphosate (GLY) is a herbicide that is widely used in agriculture for weed control. Although reports about the impact of GLY in snails, crustaceans and amphibians exist, few studies have investigated its sub-lethal effects in non-target organisms such as the honeybee Apis mellifera, the main pollen vector in commercial crops. Here, we tested whether exposure to three sub-lethal concentrations ...

Since 2006 the rate of honey bee colony failure has increased significantly. As an aid to testing hypotheses for the causes of colony failure we have developed a compartment model of honey bee colony population dynamics to explore the impact of different death rates of forager bees on colony growth and development. The model predicts a critical threshold forager death rate beneath which colonie...