Solving Five Instances of the Artificial Ant Problem with Ant Colony Optimization

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@Article{Chivilikhin:2013:PV,
  author =       "Daniil S. Chivilikhin and Vladimir I. Ulyantsev and 
                 Anatoly A. Shalyto",
  title =        "Solving Five Instances of the Artificial Ant Problem
                 with Ant Colony Optimization",
  journal =      "IFAC Proceedings Volumes",
  volume =       "46",
  number =       "9",
  pages =        "1043--1048",
  year =         "2013",
  note =         "7th IFAC Conference on Manufacturing Modelling,
                 Management, and Control",
  ISSN =         "1474-6670",
  DOI =          "doi:10.3182/20130619-3-RU-3018.00436",
  URL =          "http://www.sciencedirect.com/science/article/pii/S1474667016344275",
  abstract =     "The Artificial Ant problem is a common benchmark
                 problem often used for metaheuristic algorithm
                 performance evaluation. The problem is to find a
                 strategy controlling an agent (called an Artificial
                 Ant) in a game performed on a square toroidal field.
                 Some cells of the field contain {"}food{"} pellets,
                 which are distributed along a certain trail. In this
                 paper we use Finite-State Machines (FSM) for strategy
                 representation and present a new algorithm -MuACOsm -
                 for learning finite-state machines. The new algorithm
                 is based on an Ant Colony Optimization algorithm (ACO)
                 and a graph representation of the search space. We
                 compare the new algorithm with a genetic algorithm
                 (GA), evolutionary strategies (ES), a genetic
                 programming related approach and reinforcement learning
                 on five instances of the Artificial Ant Problem.",
  keywords =     "genetic algorithms, genetic programming, ant colony
                 optimization, automata-based programming, finite-state
                 machine, learning, induction, artificial ant problem",
}

Genetic Programming entries for Daniil Chivilikhin Vladimir Ulyantsev Anatoly Abramovich Shalyto

Citations