### Abstract

We are interested in maximizing a general (but continuous) function where observations are noisy and may be expensive. We derive a knowledge gradient policy, which chooses measurements which maximize the expected value of information, while using a locally parametric belief model which uses linear approximations around regions of the function, known as clouds. The method, called DC-RBF (Dirichlet Clouds with Radial Basis Functions) is well suited to recursive estimation, and uses a compact representation of the function which avoids storing the entire history. Our technique allows for correlated beliefs within adjacent subsets of the alternatives and does not pose any a priori assumption on the global shape of the underlying function. Experimental work suggests that the method adapts to a range of arbitrary, continuous functions, and appears to reliably find the optimal solution.

Original language | English (US) |
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Title of host publication | Proceedings of the 2013 Winter Simulation Conference - Simulation |

Subtitle of host publication | Making Decisions in a Complex World, WSC 2013 |

Pages | 856-867 |

Number of pages | 12 |

DOIs | |

State | Published - 2013 |

Event | 2013 43rd Winter Simulation Conference - Simulation: Making Decisions in a Complex World, WSC 2013 - Washington, DC, United States Duration: Dec 8 2013 → Dec 11 2013 |

### Publication series

Name | Proceedings of the 2013 Winter Simulation Conference - Simulation: Making Decisions in a Complex World, WSC 2013 |
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### Other

Other | 2013 43rd Winter Simulation Conference - Simulation: Making Decisions in a Complex World, WSC 2013 |
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Country | United States |

City | Washington, DC |

Period | 12/8/13 → 12/11/13 |

### All Science Journal Classification (ASJC) codes

- Modeling and Simulation

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## Cite this

*Proceedings of the 2013 Winter Simulation Conference - Simulation: Making Decisions in a Complex World, WSC 2013*(pp. 856-867). [6721477] (Proceedings of the 2013 Winter Simulation Conference - Simulation: Making Decisions in a Complex World, WSC 2013). https://doi.org/10.1109/WSC.2013.6721477