The effect of communication on the evolution of cooperative behavior in a multi-agent system

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@InProceedings{Goings:2014:GECCOcomp,
  author =       "Sherri Goings and Emily P. M. Johnston and 
                 Naozumi Hiranuma",
  title =        "The effect of communication on the evolution of
                 cooperative behavior in a multi-agent system",
  booktitle =    "GECCO 2014 Eighth Annual Workshop on Evolutionary
                 Computation and Multi-Agent Systems and Simulation
                 (ECoMASS)",
  year =         "2014",
  editor =       "Forrest Stonedahl and William Rand",
  isbn13 =       "978-1-4503-2881-4",
  keywords =     "genetic algorithms, genetic programming",
  pages =        "999--1006",
  month =        "12-16 " # jul,
  organisation = "SIGEVO",
  address =      "Vancouver, BC, Canada",
  URL =          "http://doi.acm.org/10.1145/2598394.2605443",
  DOI =          "doi:10.1145/2598394.2605443",
  publisher =    "ACM",
  publisher_address = "New York, NY, USA",
  abstract =     "A team of agents that cooperate to solve a problem
                 together can handle many complex tasks that would not
                 be possible without cooperation. While the benefit is
                 clear, there are still many open questions in how best
                 to achieve this cooperation. In this paper we focus on
                 the role of communication in allowing agents to evolve
                 effective cooperation for a prey capture task. Previous
                 studies of this task have shown mixed results for the
                 benefit of direct communication among predators, and we
                 investigate potential explanations for these seemingly
                 contradictory outcomes. We start by replicating the
                 results of a study that found that agents with the
                 ability to communicate actually performed worse than
                 those without when each member of a team was evolved in
                 a separate population [8]. The simulated world used for
                 these experiments is very simple, and we suggest that
                 communication would become beneficial in a similar but
                 more complex environment. We test several methods of
                 increasing the problem complexity, but find that at
                 best communicating predators perform equally as well as
                 those that cannot communicate. We thus propose that the
                 representation may hinder the success of communication
                 in this environment. The behaviour of each predator is
                 encoded in a neural network, and the networks with
                 communication have 6 inputs as opposed to just 2 for
                 the standard network, giving communicating networks
                 more than twice as many links for which to evolve
                 weights. Another study using a relatively similar
                 environment but genetic programming as a representation
                 finds that communication is clearly beneficial for prey
                 capture [4]. We suggest that adding communication is
                 less costly to these genetic programs as compared to
                 the earlier neural networks and outline experiments to
                 test this theory.",
  notes =        "Also known as \cite{2605443} Distributed at
                 GECCO-2014.",
}

Genetic Programming entries for Sherri Goings Emily P M Johnston Naozumi Hiranuma

Citations