Advertisement

Natural Computing

, 8:547 | Cite as

Natural strategies for search

  • Alec Banks
  • Jonathan VincentEmail author
  • Keith Phalp
Article

Abstract

In recent years a considerable amount of natural computing research has been undertaken to exploit the analogy between, say, searching a given problem space for an optimal solution and the natural process of foraging for food. Such analogies have led to useful solutions in areas such as optimisation, prominent examples being ant colony systems and particle swarm optimisation. However, these solutions often rely on well defined fitness landscapes that are not always be available in more general search scenarios. This paper surveys a wide variety of behaviours observed within the natural world, and aims to highlight general cooperative group behaviours, search strategies and communication methods that might be useful within a wider computing context, beyond optimisation, where information from the fitness landscape may be sparse, but new search paradigms could be developed that capitalise on research into biological systems that have developed over millennia within the natural world.

Keywords

Natural computing Search Foraging 

References

  1. Anderson C, Franks NR (2001) Teams in animal societies. Behav Ecol 12(5):534–540CrossRefGoogle Scholar
  2. Anderson C, Theraulaz G, Deneubourg JL (2002) Self-assemblages in insect societies. Insect Soc 49:99–110CrossRefGoogle Scholar
  3. Atkinson RPD, Rhodes CJ, Macdonald DW, Anderson RM (2002) Scale-free dynamics in the movement patterns of jackals. OIKOS 98:134–140CrossRefGoogle Scholar
  4. Bartumeus F, Catalan J, Fulco UL, Lyra ML, Viswanathan GM (2002) Optimizing the encounter rate in biological interactions: Lévy versus Brownian strategies. Phys Rev Lett 88:9, American Physical SocietyCrossRefGoogle Scholar
  5. Bell WJ (1991) Searching behaviour: the behavioural ecology of finding resources. Chapman and Hall Animal Behaviour Series, Chapman and Hall, LondonGoogle Scholar
  6. Benichou O, Coppey M, Moreau M, Suet P-H, Voituriez R (2005) Optimal search strategies for hidden targets. Phys Rev Lett 94:198101CrossRefGoogle Scholar
  7. Boyer D, Miramontes O, Ramos-Fernandez G, Mateos JL, Cocho G (2004) Modeling the searching behavior of social monkeys. Physica A-Statis Mech Appl 342(1–2):329–335CrossRefGoogle Scholar
  8. Burns JG (2005) Impulsive bees forage better: the advantage of quick, sometimes inaccurate foraging decisions. Anim Behav 70:e1–e5CrossRefGoogle Scholar
  9. Butler MA (2005) Foraging mode of the chameleon. Bradypodian pumilum: a challenge to the sit-and-wait versus active forager paradigm? Biol J Linn Soc 84:797–808CrossRefGoogle Scholar
  10. Charnov EL (1976) Optimal foraging, the marginal value theorem. Theor Popul Biol 9:2CrossRefGoogle Scholar
  11. Colorni A, Dorigo M, Maniezzo V (1991) Distributed optimization by ant colonies. Proc European Conference on Artificial Life, Paris, France, pp 134–142Google Scholar
  12. Cope JM, Fox CW (2003) Oviposition decisions in the seed beetle, Callosobruchus maculatus (Coleoptera: Bruchidae): effects of seed size on superparatism. J Stored Prod Res 39:355–365CrossRefGoogle Scholar
  13. De Jong K (1975) An analysis of the behaviour of a class of genetic adaptive systems. PhD thesis, University of MichiganGoogle Scholar
  14. De Meyer K, Bishop JM, Nasuto SJ (2003) Stochastic diffusion: using recruitment for search. Symposium on Evolvability & Interaction. 8–10th October 2003. Queen Mary. The University of London, UKGoogle Scholar
  15. Dechaume-Moncharmont F-X, Dornhaus A, Houston AI, McNamara JM, Collins EJ, Franks NR (2006) The hidden cost of information in collective foraging. Proc Royal Soc B Biol Sci 1(1):1689Google Scholar
  16. Dejean A, Le Breton J, Suzzoni JP, Orival J, Saux-Moreau C (2005) Influence of interspecific competition on the recruitment behavior and liquid food transport in the tramp ant species pheidole megacephala. Naturwissenschaften 92:324–327CrossRefGoogle Scholar
  17. Delestrade A (1999) Foraging strategy in a social bird the alpine chough: effect of variation in quantity and distribution of food. Anim Behav 57:299–305CrossRefGoogle Scholar
  18. Dobbs RC, Martin Te (1998) Variation in foraging behavior among nesting stages of female red-faced warblers. Condor 100:741–745, The Cooper Ornithological SocietyCrossRefGoogle Scholar
  19. Dornhaus A, Chittka L (2004) Why do honey bees dance? Behav Ecol Sociobiol 55:395–401CrossRefGoogle Scholar
  20. Dugatkin LA (1997) The evolution of cooperation. Bioscience 47(6):355 June 1997CrossRefGoogle Scholar
  21. Etiene AS, Jeffery KJ (2004) Path integration in mammals. Hippocampus 14:180–192, Wiley-Liss IncCrossRefGoogle Scholar
  22. Farina WM, Wainselboim AJ (2005) Trophallaxis within the dancing context: a behavioural and thermographic analysis in honeybees (Apis mellifera). Apidologie 36:43–47CrossRefGoogle Scholar
  23. Fitzpatrick JW (1980) Foraging behavior of neotropical tyrant flycatchers. Condor 82:43–57, The Cooper Ornithological SocietyCrossRefGoogle Scholar
  24. Fogel LJ, Owens AJ and Walsh MJ (1964) On the evolution of artificial intelligence. In: Proceedings of 5th national symposium on human factors in engineering, IEEE, San Diego, CA, pp 63–76Google Scholar
  25. Freake MJ (2001) Homing behavior in the sleepy lizard (Tiliqua rugosa): the role of visual cues and the parietal eye. Behav Ecol Sociobiol 50:563–569Google Scholar
  26. Freeman MC, Grossman GD (1992) Group foraging by a stream minnow: shoals or aggregations? Anim Behav 44:393–403CrossRefGoogle Scholar
  27. Fresneau D (1985) Individual foraging and path fidelity in a ponerine ant. Insectes Sociaux Paris 32(2):109–116CrossRefGoogle Scholar
  28. Friedberg RM (1958) A learning machine: Part I. IBM J, pp 2–13Google Scholar
  29. Fruergaard-Pedersen R (2006). Optimal demining using a swarm of low-cost robotic units. Phd Thesis, Department of Computer Science – Daimi, Faculty of Science, University of Aarhus, DenmarkGoogle Scholar
  30. Gil M, De Marco RJ (2005) Olfactory learning by means of trophallaxis in Apis mellifera. J Exp Biol 208:271–280CrossRefGoogle Scholar
  31. Gordon DM (2003) The organization of work in social insect colonies. Complexity 8(1):43–46CrossRefGoogle Scholar
  32. Grassé PP (1959) La reconstruction du nid et les coordinations interindividuelles chez bellicositermes natalensis et cubitermes sp La theorie de la stigmergie: essai d’interpretation du comportament des termites constructeurs. Insects Sociaux 6:41–81CrossRefGoogle Scholar
  33. Hauser MD (1992) Costs of deception: cheaters are punished in rhesus monkeys (Macaca mulatta). Proc Natl Acad Sci USA 89:12137–12139 CrossRefGoogle Scholar
  34. Hill S, Burrows MT, Hughes RN (2000) Increased turning per unit distance as an area-restricted search mechanism in a pause-travel predator, juvenile plaice, foraging for buried bivalves. J Fish Biol 56:1497–1508CrossRefGoogle Scholar
  35. Holland JH (1962) Outline for a logical theory of adaptive systems. J Assoc Comput Mach 3:297–314Google Scholar
  36. Holland JH (1975) Adaptation in natural and artificial systems. University of Michigan Press, Ann ArbourGoogle Scholar
  37. Holland OE, Melhuish C (1999) Stigmergy, self-organization, and sorting in collective robots. Artif Life 5:(2) 173–202Google Scholar
  38. Iwasa Y, Higashi M, Yamamura N (1981) Prey distribution as a factor determining the choice of optimal foraging strategy. Am Nat 117:710–723CrossRefMathSciNetGoogle Scholar
  39. Kennedy J, Eberhart RC (1995) Particle swarm optimization. In: Proceedings on IEEE international conference neural networks, Piscataway, NJ, pp 1942–1948Google Scholar
  40. Koza J (1992) Genetic programming: on the programming of computers by means of natural selection. MIT Press, Cambridge, MAzbMATHGoogle Scholar
  41. Krakauer DC, Rodríguez-Gironés MA (1995) Searching and learning in a random environment. J Theor Biol 177:417–419CrossRefGoogle Scholar
  42. Marchand D, McNeil JN (2004) The importance of behavioural plasticity for maximizing foraging efficiency in Frugivorous Lepidopteran Larvae. J Insect Behav 17:5CrossRefGoogle Scholar
  43. Marthaler D, Bertozzi A, Schwartz I (2004) Lévy searches based on a priori information: the biased Lévy walk. UCLA CAM Report, (04–50), 2004Google Scholar
  44. Maschwitz U, Steghaus-Kovac S, Gaube R, Hänel H (1989). A South East Asian ponerine ant of the genus Leptogenys (Hym.,Form.) with army ant life habits. Behav Ecol Sociobiol 24:305–316 CrossRefGoogle Scholar
  45. Maynard Smith J (1982) Evolution and the theory of games. Cambridge University Press, CambridgeGoogle Scholar
  46. Menzel R, Brandt R, Gumbert A, Komischke B, Kunze J (2000) Two spatial memories for honeybee navigation. Proc Royal Soc Lond B Biol Sci 267, 961–968Google Scholar
  47. Merkle T, Rost M, Alt W (2006) Egocentric path integration models and their application to desert arthropods. J Theor Biol 240:385–399CrossRefMathSciNetGoogle Scholar
  48. Minsky M (1986) The society of mind. Simon and Schuster, New YorkGoogle Scholar
  49. Mittelstaedt H (2000) Triple-loop model of path control by head direction and place cells. Biol Cybern 83:261–270CrossRefGoogle Scholar
  50. Monmarche N, Venturini G, Slimane M (2000) On how Pachycondyla apicalis ants suggest a new search algorithm. Future Gener Comp Syst 16:937–946CrossRefGoogle Scholar
  51. Morrison ML, With KA, Timossi IC. Milne KA (1987) Composition and temporal variation of flocks in the Sierra Nevada. The Condor 89:739–1450 (The Cooper Ornithological Society)CrossRefGoogle Scholar
  52. Motro U, Shmida A (1995) Near-far search–an evolutionary stable search strategy. J Theor Biol 173:15–22CrossRefGoogle Scholar
  53. Müller M, Wehner R (1994) The hidden spiral: systematic search and path integration in desert ants, Cataglyphis fortis. J Compar Physiol A: Neuroethol, Sensory, Neural, Behav Physiol. 175(5)Google Scholar
  54. Nishimura K (1999) Exploration of optimal giving-up time in uncertain environment: a sit-and-wait forager. J Theor Biol 199:321–327CrossRefGoogle Scholar
  55. O’Brien JW, Browman HI, Evans BI (1990) Search strategies of foraging animals. Am Scient 78:152–160Google Scholar
  56. Papaj DR, Rausher MD (1983) Individual variation in host location by phytophagous insects. In: Ahmad S (ed) Herbivorous Insects, Host-Seeking Behavior and Mechanisms. pp 77–124Google Scholar
  57. Passino KM (2002) Biomimicry of bacterial foraging for distributed optimisation and control. IEEE Cont Syst Magazine, June 2002, pp 52 –67Google Scholar
  58. Pianka ER (1966) Convexity, desert lizards, and spatial heterogeneity. Ecology 47:1055–1059CrossRefGoogle Scholar
  59. Pyke GH (1978) Optimal foraging: movement patterns of bumblebees between inflorescences. Theor Popul Biol 13:72–98CrossRefGoogle Scholar
  60. Ramos-Fernández G, Mateos JL, Miramontes O, Cocho G, Larralde H, Ayala-Orozco B (2004) Lévy walk patterns in the foraging movements of spider monkeys (Ateles geoffroyi). Behav Ecol Sociobiol 55:223CrossRefGoogle Scholar
  61. Rechenberg I (1965) Cybernetic solution path of an experimental problem. Royal Aircraft Establishment, Library Translation No. 1122 Google Scholar
  62. Reed HC, Landolt PJ (2000) Application of alarm pheromone to targets by southern yellowjackets (Hymenoptera: Vespidae). Fla Entomol 83(2):193–196CrossRefGoogle Scholar
  63. Sandia National Laboratories (2001) Developing technologies for asymmetrical warfare and homeland defense. Sandia Technology vol 3, no 2. Sandia National Laboratories. Albuquerque, USAGoogle Scholar
  64. Secor SM (1994) Ecological significance of movements and activity range for the sidewinder, Crotalus cerastes. Copeia 1994(3):631–645CrossRefGoogle Scholar
  65. Schmickl T, Crailsheim K (2006) Trophallaxis among swarm-robots: a biologically inspired strategy for swarm robotics. BioRob 2006, The First IEEE/RAS-EMBS International Conference on Biomedical Robotics and Biomechatronics, 2006. February 20–22, 2006, pp 377–382Google Scholar
  66. Skutelsky O (1995) Flexibility in foraging tactics of Buthus Occitanus scorpions as a response to above-ground activity of termites. J Arachnol 23:46–47Google Scholar
  67. Stahl JC, Sagar PM (2000) Foraging strategies if southern Buller’s albatrosses Diomedea b. bulleri breeding on The Snares, New Zealand. J Royal Soc NZ 30(3):299–318Google Scholar
  68. Steinmetz I, Schmolz E, Ruther J (2003) Cuticular lipids as trail pheromone in a social wasp. Proc Royal Soc London B 270:385–291CrossRefGoogle Scholar
  69. Stevens JR, Cushman FA, Hauser MD (2005) Evolving the psychological mechanisms for cooperation. Annu Rev Ecol Evol Syst 36:499–518CrossRefGoogle Scholar
  70. Viswanathan GM, Buldyrev SV, Havlin S, Da Luz MGE, Raposo EP, Stanley HE (1999) Optimizing the success of random searches. Nature 401:911–914CrossRefGoogle Scholar
  71. Viswanathan GM, Afanasyev V, Buldyrev SV, Havlin S, da Luz MGE, Raposo EP, Stanley HE (2001) Lévy flights search patterns of biological organisms. Physica A 295:85–88CrossRefzbMATHGoogle Scholar
  72. Viswanathan GM, Bartumeus F, Buldyrev SV, Catalan J, Fulco UL, Havlin S, da Luz MGE, Lyra ML, Raposo EP, Stanley HE (2002) Lévy flight random searches in biological phenomena. Physica A 314:208–213CrossRefMathSciNetzbMATHGoogle Scholar
  73. Von Frisch K (1967) The dance language and orientation of bees. Harvard University Press. Cambridge, Massachusetts, USAGoogle Scholar
  74. Vladusich T, Hemmi JM, Zeil J (2006) Honeybee odometry and scent guidance. J Exp Biol 209:1367–1375CrossRefGoogle Scholar
  75. Waddington KD (1980) Flight patterns of foraging bees relative to density of artificial flowers and distribution of nectar. Oecologia (Berl) 44:199–204CrossRefGoogle Scholar
  76. Waibel M, Floreano D, Magnenat S, Keller L (2006) Division of labour and colony efficiency in social insects: effects of interactions between genetic architecture, colony kin structure and rate of perturbations. Proc Royal Soc B 273, 1815–1823Google Scholar
  77. Ward P, Zahavi A (1973) The importance of certain assemblages of birds as ‘information centres’ for food finding. Ibis 117:517–534CrossRefGoogle Scholar
  78. Wiess MR, Papaj DR (2003) Colour learning in two behavioural contexts: how much can a butterfly keep in mind? Anim Behav 65:425–434CrossRefGoogle Scholar
  79. Wolpert DH, Macready WG (1997) No free lunch theorems for optimization. IEEE Trans Evolut Comput 1(1):67–82CrossRefGoogle Scholar
  80. Wright J, Stone RE, Brown N (2003) Communal roosts as structured information centres in the raven, Corvus corax. J Anim Ecol 72:1003–1014CrossRefGoogle Scholar
  81. Zamon JE (2001) Seal predation on salmon and forage fish schools as a function of tidal currents in the San Juan Islands, Washington, USA. Fish Oceanogr 10(4):353–366CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2008

Authors and Affiliations

  1. 1.Software Systems Research Centre, School of Design, Engineering and ComputingBournemouth UniversityPoole, DorsetUK

Personalised recommendations