### Abstract

We are developing a new problem-solving methodology based on a self-organization paradigm. To realize our future goal of self-organizing computational systems, we have to study computation based on local information and its emergent behavior, which are considered essential in self-organizing systems. This paper presents a stochastic (or nondeterministic) problem solving method using local operations and local evaluation functions. Several constraint satisfaction problems are solved and approximate solutions of several optimization problem are found by this method in polynomial order time in average. Major features of this method are as follows. Problems can be solved using one or a few simple production rules and evaluation functions, both of which work locally, i.e., on a small number of objects. Local maxima of the sum of evaluation function values can sometimes be avoided. Limit cycles of execution can also be avoided. There are two methods for changing the locality of rules. The efficiency of searches and the possibility of falling into local maxima can be controlled by changing the locality.

Original language | English |
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Title of host publication | Proceedings of the Hawaii International Conference on System Sciences |

Editors | Jay F. Nunamaker, Ralph H.Jr. Sprague |

Publisher | Publ by IEEE |

Pages | 82-91 |

Number of pages | 10 |

ISBN (Print) | 0818650702 |

Publication status | Published - Jan 1 1994 |

Externally published | Yes |

Event | Proceedings of the 27th Hawaii International Conference on System Sciences (HICSS-27). Part 4 (of 5) - Wailea, HI, USA Duration: Jan 4 1994 → Jan 7 1994 |

### Publication series

Name | Proceedings of the Hawaii International Conference on System Sciences |
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Volume | 3 |

ISSN (Print) | 1060-3425 |

### Other

Other | Proceedings of the 27th Hawaii International Conference on System Sciences (HICSS-27). Part 4 (of 5) |
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City | Wailea, HI, USA |

Period | 1/4/94 → 1/7/94 |

### Fingerprint

### All Science Journal Classification (ASJC) codes

- Computer Science(all)

### Cite this

*Proceedings of the Hawaii International Conference on System Sciences*(pp. 82-91). (Proceedings of the Hawaii International Conference on System Sciences; Vol. 3). Publ by IEEE.

**Stochastic problem solving by local computation based on self-organization paradigm.** / Kanada, Yasusi; Hirokawa, Masao.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

*Proceedings of the Hawaii International Conference on System Sciences.*Proceedings of the Hawaii International Conference on System Sciences, vol. 3, Publ by IEEE, pp. 82-91, Proceedings of the 27th Hawaii International Conference on System Sciences (HICSS-27). Part 4 (of 5), Wailea, HI, USA, 1/4/94.

}

TY - GEN

T1 - Stochastic problem solving by local computation based on self-organization paradigm

AU - Kanada, Yasusi

AU - Hirokawa, Masao

PY - 1994/1/1

Y1 - 1994/1/1

N2 - We are developing a new problem-solving methodology based on a self-organization paradigm. To realize our future goal of self-organizing computational systems, we have to study computation based on local information and its emergent behavior, which are considered essential in self-organizing systems. This paper presents a stochastic (or nondeterministic) problem solving method using local operations and local evaluation functions. Several constraint satisfaction problems are solved and approximate solutions of several optimization problem are found by this method in polynomial order time in average. Major features of this method are as follows. Problems can be solved using one or a few simple production rules and evaluation functions, both of which work locally, i.e., on a small number of objects. Local maxima of the sum of evaluation function values can sometimes be avoided. Limit cycles of execution can also be avoided. There are two methods for changing the locality of rules. The efficiency of searches and the possibility of falling into local maxima can be controlled by changing the locality.

AB - We are developing a new problem-solving methodology based on a self-organization paradigm. To realize our future goal of self-organizing computational systems, we have to study computation based on local information and its emergent behavior, which are considered essential in self-organizing systems. This paper presents a stochastic (or nondeterministic) problem solving method using local operations and local evaluation functions. Several constraint satisfaction problems are solved and approximate solutions of several optimization problem are found by this method in polynomial order time in average. Major features of this method are as follows. Problems can be solved using one or a few simple production rules and evaluation functions, both of which work locally, i.e., on a small number of objects. Local maxima of the sum of evaluation function values can sometimes be avoided. Limit cycles of execution can also be avoided. There are two methods for changing the locality of rules. The efficiency of searches and the possibility of falling into local maxima can be controlled by changing the locality.

UR - http://www.scopus.com/inward/record.url?scp=0028015041&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0028015041&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:0028015041

SN - 0818650702

T3 - Proceedings of the Hawaii International Conference on System Sciences

SP - 82

EP - 91

BT - Proceedings of the Hawaii International Conference on System Sciences

A2 - Nunamaker, Jay F.

A2 - Sprague, Ralph H.Jr.

PB - Publ by IEEE

ER -