Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/99222
Title: Computational studies of exploration by smell
Authors: Leow, W.K. 
Keywords: Danger avoidance
Emergent behaviors
Exploration by smell
Obstacle negotiation
Olfactory-motor coordination
Risk taking
Issue Date: Dec-1998
Source: Leow, W.K. (1998-12). Computational studies of exploration by smell. Adaptive Behavior 6 (3-4) : 411-434. ScholarBank@NUS Repository.
Abstract: Research on exploratory and searching behavior of animals and robots has attracted an increasing amount of interest recently. Existing works have focused mostly on exploratory behavior guided by vision and audition. Research on smell-guided exploration has been lacking, even though animals may use the sense of smell more widely than sight or hearing to search for food and to evade danger. This article contributes to the study of smell-guided exploration. It describes a series of increasingly complex neural networks, each of which allows a simulated creature to search for food and to evade danger by using smell. Other behaviors such as obstacle negotiation and risk taking emerge naturally from the creature's interaction with the environment. Comparative studies of these networks show that there is no significant performance advantage for a creature to have more than two sensors. This result may help to explain why real animals have only one or two smell-sensing organs.
Source Title: Adaptive Behavior
URI: http://scholarbank.nus.edu.sg/handle/10635/99222
ISSN: 10597123
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.

Page view(s)

33
checked on Mar 9, 2018

Google ScholarTM

Check


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.