Analyzing Sensor States and Internal States in the Tartarus Problem with Tree State Machines

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@InProceedings{Kim:PPSN:2004,
  author =       "DaeEun Kim",
  title =        "Analyzing Sensor States and Internal States in the
                 Tartarus Problem with Tree State Machines",
  booktitle =    "Parallel Problem Solving from Nature - PPSN VIII",
  year =         "2004",
  editor =       "Xin Yao and Edmund Burke and Jose A. Lozano and 
                 Jim Smith and Juan J. Merelo-Guerv\'os and 
                 John A. Bullinaria and Jonathan Rowe and 
                 Peter Ti\v{n}o Ata Kab\'an and Hans-Paul Schwefel",
  volume =       "3242",
  pages =        "551--560",
  series =       "LNCS",
  address =      "Birmingham, UK",
  publisher_address = "Berlin",
  month =        "18-22 " # sep,
  publisher =    "Springer-Verlag",
  ISBN =         "3-540-23092-0",
  keywords =     "genetic algorithms, genetic programming",
  URL =          "http://www.springerlink.com/openurl.asp?genre=article&issn=0302-9743&volume=3242&spage=551",
  DOI =          "doi:10.1007/b100601",
  abstract =     "The Tartarus problem is a box pushing task in a grid
                 world environment. It is one of difficult problems for
                 purely reactive agents to solve, and thus a
                 memory-based control architecture is required. This
                 paper presents a novel control structure, called tree
                 state machine, which has an evolving tree structure for
                 sensorimotor mapping and also encodes internal states.
                 As a result, the evolutionary computation on tree state
                 machines can quantify internal states and sensor states
                 needed for the problem. Tree state machines with a
                 dynamic feature of sensor states are demonstrated and
                 compared with finite state machines and GP-automata. It
                 is shown that both sensor states and memory states are
                 important factors to influence the behaviour
                 performance of an agent.",
  notes =        "PPSN-VIII",
}

Genetic Programming entries for DaeEun Kim

Citations