Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Abductive inference in Bayesian belief networks is the process of generating the K most probable configurations given an observed evidence. When  are only interested in a subset of the network’s variables, this problem is called partial abductive inference. Both problems are NP-hard, and so exact computation is not always possible.  describes an approximate method based on genetic algorithms to perform partial abductive inference.  have tested the algorithm using the alarm network and from the experimental results  can conclude that the algorithm presented here is a good tool to perform this kind of probabilistic reasoning. ” 1999 Elsevier Science B.V. All rights reserved.
['L. M. de Campos', 'José A. Gámez', 'S. Moral']
I am writing a research paper on a idea Partial abductive inference in Bayesian belief networks using a genetic algorithm
[{"from": "human", "value": "I am writing a research paper on a idea Partial abductive inference in Bayesian belief networks using a genetic algorithm"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Abductive inference in Bayesian belief networks is the process of generating the K most probable configurations given an observed evidence. When  are only interested in a subset of the network\u2019s variables, this problem is called partial abductive inference. Both problems are NP-hard, and so exact computation is not always possible.  describes an approximate method based on genetic algorithms to perform partial abductive inference.  have tested the algorithm using the alarm network and from the experimental results  can conclude that the algorithm presented here is a good tool to perform this kind of probabilistic reasoning. \u201d 1999 Elsevier Science B.V. All rights reserved."}]