All

What are you looking for?

All
Projects
Results
Organizations

Quick search

  • Projects supported by TA ČR
  • Excellent projects
  • Projects with the highest public support
  • Current projects

Smart search

  • That is how I find a specific +word
  • That is how I leave the -word out of the results
  • “That is how I can find the whole phrase”

2D P Colony for Vicinity Search Optimisation

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F47813059%3A19240%2F24%3AA0001388" target="_blank" >RIV/47813059:19240/24:A0001388 - isvavai.cz</a>

  • Result on the web

    <a href="https://webusers.i3s.unice.fr/CMC2024/accepted/" target="_blank" >https://webusers.i3s.unice.fr/CMC2024/accepted/</a>

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    2D P Colony for Vicinity Search Optimisation

  • Original language description

    P colony is a formal computational model suitable for modelling behaviour of simple agents acting in a shared environment. We build on the original concept of formal colonies where both the environment and agents were implemented by tools of formal grammars. P colonies transformed this concept into the framework of membrane systems, i.e., the environment and agents contain abstract discrete objects and formal rules acting upon them. Adding a 2D geometrical structure and evolution of the environment resulted in the model of 2D evolving P colonies. The model is suitable for simulation of phenomena like stigmergy, hence also for implementation of multi-agent optimisation strategies. The motivation for such an implementation lies in a possible future highly parallel and efficient bio-hardware implementation of P systems. In this paper we use a 2D P colony to implement an ant colony-inspired optimisation algorithm. The agents– ants– search the environment for food representing extrema of the objective function. The search is oriented with the help of pheromone trails left by previous agents. The trails are subject to a decay and they can eventually vanish. The original formulation of ant algorithms counts on ants immediately collecting found food in the nest. Here we allow the ants to decide randomly whether to collect the food or to continue the search for another food in the vicinity of an already found food source. We demonstrate experimentally that this behaviour improves the search results.

  • Czech name

  • Czech description

Classification

  • Type

    O - Miscellaneous

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

  • Continuities

    S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2024

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů