The Automatic Programming of Agents that Learn Mental Models and Create Simple Plans of Action

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

@InProceedings{andre:1995:apalmm,
  author =       "David Andre",
  title =        "The Automatic Programming of Agents that Learn Mental
                 Models and Create Simple Plans of Action",
  booktitle =    "IJCAI-95 Proceedings of the Fourteenth International
                 Joint Conference on Artificial Intelligence",
  year =         "1995",
  volume =       "1",
  pages =        "741--747",
  address =      "Montreal, Quebec, Canada",
  publisher_address = "San Francisco, CA, USA",
  month =        "20-25 " # aug,
  organisation = "IJCAII,AAAI,CSCSI",
  publisher =    "Morgan Kaufmann",
  keywords =     "genetic algorithms, genetic programming, memory",
  ISBN =         "1-55860-363-8",
  URL =          "http://ijcai.org/Past%20Proceedings/IJCAI-95-VOL%201/pdf/097.pdf",
  size =         "7 pages",
  abstract =     "An essential component of an intelligent agent is the
                 ability to notice, encode, store, and use information
                 about its environment. Traditional approaches to
                 program induction have focused on evolving functional
                 or reactive programs. This paper presents MAPMAKER, a
                 method for the automatic generation of agents that
                 discover information about their environment, encode
                 this information for later use, and create simple plans
                 using the stored mental models. In this method, agents
                 are multi-part computer programs that communicate
                 through a shared memory. Both the programs and the
                 representation scheme are evolved using genetic
                 programming. An illustrative problem of 'gold'
                 collection is used to demonstrate the method in which
                 one part of a program makes a map of the world and
                 stores it in memory, and the other part uses this map
                 to find the gold The results indicate that the method
                 can evolve programs that store simple representations
                 of their environments and use these representations to
                 produce simple plans.",
  notes =        "MAPMAKER searches for gold",
}

Genetic Programming entries for David Andre

Citations