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Cites:

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Information Journal Paper

Title

LEANING THE STRUCTURE OF BAYESIAN NETWORKS USING LEARNING AUTOMATA

Author(s)

MEYBODI M.R. target="_blank">MOLLAKHALILI MEYBODI M.R. | MEYBODI M.R. | Issue Writer Certificate 

Pages

  27-40

Abstract

 The structure of a BAYESIAN NETWORK represents a set of conditional independence relations that hold in the domain. Learning the structure of the BAYESIAN NETWORK model that represents a domain can reveal in sights into its underlying causal structure. Automatically learning the graph structure of a BAYESIAN NETWORK is a challenge pursued within artificial intelligence studies. In this paper, a new algorithm based on LEARNING AUTOMATA is proposed for learning the structure of the BAYESIAN NETWORKs. In this algorithm, automata is used as a tool for searching in structure’s space (DAG’s space) of the BAYESIAN NETWORKs. The mathematical behavior of the proposed algorithm is studied.

Cites

References

Cite

APA: Copy

MOLLAKHALILI MEYBODI, M.R., & MEYBODI, M.R.. (2016). LEANING THE STRUCTURE OF BAYESIAN NETWORKS USING LEARNING AUTOMATA. NASHRIYYAH -I MUHANDISI -I BARQ VA MUHANDISI -I KAMPYUTAR -I IRAN, B- MUHANDISI -I KAMPYUTAR, 14(1), 27-40. SID. https://sid.ir/paper/228524/en

Vancouver: Copy

MOLLAKHALILI MEYBODI M.R., MEYBODI M.R.. LEANING THE STRUCTURE OF BAYESIAN NETWORKS USING LEARNING AUTOMATA. NASHRIYYAH -I MUHANDISI -I BARQ VA MUHANDISI -I KAMPYUTAR -I IRAN, B- MUHANDISI -I KAMPYUTAR[Internet]. 2016;14(1):27-40. Available from: https://sid.ir/paper/228524/en

IEEE: Copy

M.R. MOLLAKHALILI MEYBODI, and M.R. MEYBODI, “LEANING THE STRUCTURE OF BAYESIAN NETWORKS USING LEARNING AUTOMATA,” NASHRIYYAH -I MUHANDISI -I BARQ VA MUHANDISI -I KAMPYUTAR -I IRAN, B- MUHANDISI -I KAMPYUTAR, vol. 14, no. 1, pp. 27–40, 2016, [Online]. Available: https://sid.ir/paper/228524/en

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