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Natural strategies for search

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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.

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References

  • Anderson C, Franks NR (2001) Teams in animal societies. Behav Ecol 12(5):534–540

    Article  Google Scholar 

  • Anderson C, Theraulaz G, Deneubourg JL (2002) Self-assemblages in insect societies. Insect Soc 49:99–110

    Article  Google Scholar 

  • Atkinson RPD, Rhodes CJ, Macdonald DW, Anderson RM (2002) Scale-free dynamics in the movement patterns of jackals. OIKOS 98:134–140

    Article  Google Scholar 

  • 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 Society

    Article  Google Scholar 

  • Bell WJ (1991) Searching behaviour: the behavioural ecology of finding resources. Chapman and Hall Animal Behaviour Series, Chapman and Hall, London

    Google Scholar 

  • Benichou O, Coppey M, Moreau M, Suet P-H, Voituriez R (2005) Optimal search strategies for hidden targets. Phys Rev Lett 94:198101

    Article  Google Scholar 

  • 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):329–335

    Article  Google Scholar 

  • Burns JG (2005) Impulsive bees forage better: the advantage of quick, sometimes inaccurate foraging decisions. Anim Behav 70:e1–e5

    Article  Google Scholar 

  • 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 84:797–808

    Article  Google Scholar 

  • Charnov EL (1976) Optimal foraging, the marginal value theorem. Theor Popul Biol 9:2

    Article  Google Scholar 

  • Colorni A, Dorigo M, Maniezzo V (1991) Distributed optimization by ant colonies. Proc European Conference on Artificial Life, Paris, France, pp 134–142

    Google Scholar 

  • 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 39:355–365

    Article  Google Scholar 

  • De Jong K (1975) An analysis of the behaviour of a class of genetic adaptive systems. PhD thesis, University of Michigan

  • 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, UK

  • 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):1689

    Google Scholar 

  • 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 92:324–327

    Article  Google Scholar 

  • Delestrade A (1999) Foraging strategy in a social bird the alpine chough: effect of variation in quantity and distribution of food. Anim Behav 57:299–305

    Article  Google Scholar 

  • Dobbs RC, Martin Te (1998) Variation in foraging behavior among nesting stages of female red-faced warblers. Condor 100:741–745, The Cooper Ornithological Society

    Article  Google Scholar 

  • Dornhaus A, Chittka L (2004) Why do honey bees dance? Behav Ecol Sociobiol 55:395–401

    Article  Google Scholar 

  • Dugatkin LA (1997) The evolution of cooperation. Bioscience 47(6):355 June 1997

    Article  Google Scholar 

  • Etiene AS, Jeffery KJ (2004) Path integration in mammals. Hippocampus 14:180–192, Wiley-Liss Inc

    Article  Google Scholar 

  • Farina WM, Wainselboim AJ (2005) Trophallaxis within the dancing context: a behavioural and thermographic analysis in honeybees (Apis mellifera). Apidologie 36:43–47

    Article  Google Scholar 

  • Fitzpatrick JW (1980) Foraging behavior of neotropical tyrant flycatchers. Condor 82:43–57, The Cooper Ornithological Society

    Article  Google Scholar 

  • 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 63–76

  • Freake MJ (2001) Homing behavior in the sleepy lizard (Tiliqua rugosa): the role of visual cues and the parietal eye. Behav Ecol Sociobiol 50:563–569

    Google Scholar 

  • Freeman MC, Grossman GD (1992) Group foraging by a stream minnow: shoals or aggregations? Anim Behav 44:393–403

    Article  Google Scholar 

  • Fresneau D (1985) Individual foraging and path fidelity in a ponerine ant. Insectes Sociaux Paris 32(2):109–116

    Article  Google Scholar 

  • Friedberg RM (1958) A learning machine: Part I. IBM J, pp 2–13

  • 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, Denmark

  • Gil M, De Marco RJ (2005) Olfactory learning by means of trophallaxis in Apis mellifera. J Exp Biol 208:271–280

    Article  Google Scholar 

  • Gordon DM (2003) The organization of work in social insect colonies. Complexity 8(1):43–46

    Article  Google Scholar 

  • 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 6:41–81

    Article  Google Scholar 

  • Hauser MD (1992) Costs of deception: cheaters are punished in rhesus monkeys (Macaca mulatta). Proc Natl Acad Sci USA 89:12137–12139

    Article  Google Scholar 

  • 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 56:1497–1508

    Article  Google Scholar 

  • Holland JH (1962) Outline for a logical theory of adaptive systems. J Assoc Comput Mach 3:297–314

    Google Scholar 

  • Holland JH (1975) Adaptation in natural and artificial systems. University of Michigan Press, Ann Arbour

    Google Scholar 

  • Holland OE, Melhuish C (1999) Stigmergy, self-organization, and sorting in collective robots. Artif Life 5:(2) 173–202

    Google Scholar 

  • Iwasa Y, Higashi M, Yamamura N (1981) Prey distribution as a factor determining the choice of optimal foraging strategy. Am Nat 117:710–723

    Article  MathSciNet  Google Scholar 

  • Kennedy J, Eberhart RC (1995) Particle swarm optimization. In: Proceedings on IEEE international conference neural networks, Piscataway, NJ, pp 1942–1948

  • Koza J (1992) Genetic programming: on the programming of computers by means of natural selection. MIT Press, Cambridge, MA

    MATH  Google Scholar 

  • Krakauer DC, Rodríguez-Gironés MA (1995) Searching and learning in a random environment. J Theor Biol 177:417–419

    Article  Google Scholar 

  • Marchand D, McNeil JN (2004) The importance of behavioural plasticity for maximizing foraging efficiency in Frugivorous Lepidopteran Larvae. J Insect Behav 17:5

    Article  Google Scholar 

  • Marthaler D, Bertozzi A, Schwartz I (2004) Lévy searches based on a priori information: the biased Lévy walk. UCLA CAM Report, (04–50), 2004

  • 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

    Article  Google Scholar 

  • Maynard Smith J (1982) Evolution and the theory of games. Cambridge University Press, Cambridge

  • 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, 961–968

    Google Scholar 

  • Merkle T, Rost M, Alt W (2006) Egocentric path integration models and their application to desert arthropods. J Theor Biol 240:385–399

    Article  MathSciNet  Google Scholar 

  • Minsky M (1986) The society of mind. Simon and Schuster, New York

    Google Scholar 

  • Mittelstaedt H (2000) Triple-loop model of path control by head direction and place cells. Biol Cybern 83:261–270

    Article  Google Scholar 

  • Monmarche N, Venturini G, Slimane M (2000) On how Pachycondyla apicalis ants suggest a new search algorithm. Future Gener Comp Syst 16:937–946

    Article  Google Scholar 

  • 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)

    Article  Google Scholar 

  • Motro U, Shmida A (1995) Near-far search–an evolutionary stable search strategy. J Theor Biol 173:15–22

    Article  Google Scholar 

  • 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)

  • Nishimura K (1999) Exploration of optimal giving-up time in uncertain environment: a sit-and-wait forager. J Theor Biol 199:321–327

    Article  Google Scholar 

  • O’Brien JW, Browman HI, Evans BI (1990) Search strategies of foraging animals. Am Scient 78:152–160

    Google Scholar 

  • 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 77–124

  • Passino KM (2002) Biomimicry of bacterial foraging for distributed optimisation and control. IEEE Cont Syst Magazine, June 2002, pp 52 –67

  • Pianka ER (1966) Convexity, desert lizards, and spatial heterogeneity. Ecology 47:1055–1059

    Article  Google Scholar 

  • Pyke GH (1978) Optimal foraging: movement patterns of bumblebees between inflorescences. Theor Popul Biol 13:72–98

    Article  Google Scholar 

  • 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 55:223

    Article  Google Scholar 

  • Rechenberg I (1965) Cybernetic solution path of an experimental problem. Royal Aircraft Establishment, Library Translation No. 1122

  • Reed HC, Landolt PJ (2000) Application of alarm pheromone to targets by southern yellowjackets (Hymenoptera: Vespidae). Fla Entomol 83(2):193–196

    Article  Google Scholar 

  • Sandia National Laboratories (2001) Developing technologies for asymmetrical warfare and homeland defense. Sandia Technology vol 3, no 2. Sandia National Laboratories. Albuquerque, USA

  • Secor SM (1994) Ecological significance of movements and activity range for the sidewinder, Crotalus cerastes. Copeia 1994(3):631–645

    Article  Google Scholar 

  • 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 377–382

  • Skutelsky O (1995) Flexibility in foraging tactics of Buthus Occitanus scorpions as a response to above-ground activity of termites. J Arachnol 23:46–47

    Google Scholar 

  • 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):299–318

    Google Scholar 

  • Steinmetz I, Schmolz E, Ruther J (2003) Cuticular lipids as trail pheromone in a social wasp. Proc Royal Soc London B 270:385–291

    Article  Google Scholar 

  • Stevens JR, Cushman FA, Hauser MD (2005) Evolving the psychological mechanisms for cooperation. Annu Rev Ecol Evol Syst 36:499–518

    Article  Google Scholar 

  • Viswanathan GM, Buldyrev SV, Havlin S, Da Luz MGE, Raposo EP, Stanley HE (1999) Optimizing the success of random searches. Nature 401:911–914

    Article  Google Scholar 

  • 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 295:85–88

    Article  MATH  Google Scholar 

  • 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 314:208–213

    Article  MathSciNet  MATH  Google Scholar 

  • Von Frisch K (1967) The dance language and orientation of bees. Harvard University Press. Cambridge, Massachusetts, USA

    Google Scholar 

  • Vladusich T, Hemmi JM, Zeil J (2006) Honeybee odometry and scent guidance. J Exp Biol 209:1367–1375

    Article  Google Scholar 

  • Waddington KD (1980) Flight patterns of foraging bees relative to density of artificial flowers and distribution of nectar. Oecologia (Berl) 44:199–204

    Article  Google Scholar 

  • 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, 1815–1823

    Google Scholar 

  • Ward P, Zahavi A (1973) The importance of certain assemblages of birds as ‘information centres’ for food finding. Ibis 117:517–534

    Article  Google Scholar 

  • Wiess MR, Papaj DR (2003) Colour learning in two behavioural contexts: how much can a butterfly keep in mind? Anim Behav 65:425–434

    Article  Google Scholar 

  • Wolpert DH, Macready WG (1997) No free lunch theorems for optimization. IEEE Trans Evolut Comput 1(1):67–82

    Article  Google Scholar 

  • Wright J, Stone RE, Brown N (2003) Communal roosts as structured information centres in the raven, Corvus corax. J Anim Ecol 72:1003–1014

    Article  Google Scholar 

  • 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):353–366

    Article  Google Scholar 

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  1. Software Systems Research Centre, School of Design, Engineering and Computing, Bournemouth University, Fern Barrow, Poole, Dorset, BH12 5BB, UK

    Alec Banks, Jonathan Vincent & Keith Phalp

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  1. Alec Banks
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  2. Jonathan Vincent
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  3. Keith Phalp
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Correspondence to Jonathan Vincent.

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Banks, A., Vincent, J. & Phalp, K. Natural strategies for search. Nat Comput 8, 547–570 (2009). https://doi.org/10.1007/s11047-008-9087-7

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