• DocumentCode
    2307252
  • Title

    Think globally, sense locally: From local information to global features

  • Author

    Harder, Malte ; Polani, Daniel ; Nehaniv, Chrystopher L.

  • Author_Institution
    Adaptive Syst. Res. Group, Univ. of Hertfordshire, Hatfield, UK
  • fYear
    2011
  • fDate
    11-15 April 2011
  • Firstpage
    70
  • Lastpage
    77
  • Abstract
    Shannon´s information theory can be used to quantify morphological and topological features of a collective of agents in an arbitrary environment. In particular the ability of individual agents to extract information locally about global features of the collective can be quantified. Here, we considered chains of agents in a grid world. The agents are equipped with local sensors. We then quantified the amount of information the sensors contain about certain features global to the chain. Furthermore, we compared the amount of locally available information to the amount of information the whole collective could in principle acquire about a feature in different contexts.
  • Keywords
    information theory; mathematical morphology; sensors; Shannon information theory; global feature; information extraction; morphological feature; sensor; topological feature; Entropy; Information theory; Random variables; Sensor phenomena and characterization; Shape; Uncertainty;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Artificial Life (ALIFE), 2011 IEEE Symposium on
  • Conference_Location
    Paris
  • ISSN
    2160-6374
  • Print_ISBN
    978-1-61284-062-8
  • Type

    conf

  • DOI
    10.1109/ALIFE.2011.5954661
  • Filename
    5954661