Investigating the evolution of animal behavior is difficult. The fossil record leaves few clues that would allow us to recapitulate the path that evolution took to build a complex behavior, and the large population sizes and long time scales required prevent us from re-evolving such behaviors in a laboratory setting. We present results of a study in which digital organisms-self-replicating computer programs that are subject to mutations and selection-evolved in different environments that required information about past experience for fitness-enhancing behavioral decisions. One population evolved a mechanism for step-counting, a surprisingly complex odometric behavior that was only indirectly related to enhancing fitness. We examine in detail the operation of the evolved mechanism and the evolutionary transitions that produced this striking example of a complex behavior.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3620120 | PMC |
http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0060466 | PLOS |
Front Neurorobot
April 2017
IBM ResearchTokyo, Japan.
Despite their small size, insect brains are able to produce robust and efficient navigation in complex environments. Specifically in social insects, such as ants and bees, these navigational capabilities are guided by orientation directing vectors generated by a process called path integration. During this process, they integrate compass and odometric cues to estimate their current location as a vector, called the home vector for guiding them back home on a straight path.
View Article and Find Full Text PDFPLoS One
October 2013
Department of Computer Science, University of Texas-Pan American, Edinburg, Texas, USA.
Investigating the evolution of animal behavior is difficult. The fossil record leaves few clues that would allow us to recapitulate the path that evolution took to build a complex behavior, and the large population sizes and long time scales required prevent us from re-evolving such behaviors in a laboratory setting. We present results of a study in which digital organisms-self-replicating computer programs that are subject to mutations and selection-evolved in different environments that required information about past experience for fitness-enhancing behavioral decisions.
View Article and Find Full Text PDFJ Exp Biol
April 2008
Centre for Brain and Behaviour, Department of Physiology, Monash University, Clayton 3800, VI, Australia.
The ability to navigate long distances to find rewarding flowers and return home is a key factor in the survival of honeybees (Apis mellifera). To reliably perform this task, bees combine both odometric and landmark cues, which potentially creates a dilemma since environments rich in odometric cues might be poor in salient landmark cues, and vice versa. In the present study, honeybees were provided with differential conditioning to images of complex natural scenes, in order to determine if they could reliably learn to discriminate between very similar scenes, and to recognise a learnt scene from a novel distractor scene.
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