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public:t-720-atai:atai-19:final_project [2019/10/28 19:59]
thorisson [NARS Assignment 2: Diagnosis]
public:t-720-atai:atai-19:final_project [2019/10/28 20:03] (current)
thorisson [NARS Assignment 2: Diagnosis]
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 Make sure you have studied Xiang Li's {{/public:t-720-atai:nars-tutorial.pdf|NARS Tutorial}} notes. Make sure you have studied Xiang Li's {{/public:t-720-atai:nars-tutorial.pdf|NARS Tutorial}} notes.
-In this project, students are required to generate a car diagnostic system with OpenNARS.    The detailed car use case breaks down the object to be diagnosedthe car, according to the following diagramIn this diagramtwo types of nodes existone denoting a componentand one denoting ‘observation’These nodes represent items that would be ‘sensed’ by user of the vehicleThis list was created from the point of view of a lay user describing issues to a mechanic, and try to reflect the high level indicators that exist on common dashboards.  +In this project you will generate a diagnostic system with OpenNARS. Use the medical diagnostic example and the description about the Car diagnostic system as hints to design a diagnostic system for Carstest it with OpenNARS. Try to come up with good alternative examples, for instance the following
 +1Different type of cars (SedanSport, Truck) may have different possibility of having different problems when same symptoms show upfor instanceadults have higher possibility to get HIV than childrenIf Dan has same symptom with John but Dan is child, will Dan have same disease with John?  
 +2. In the medical diagnostic example, default truth values (f = 1.0, c = 0.9) are attached to all the statements of John’s symptoms, if we change those statements to statements where true to the degree. 
 +3. If we already know what disease that John has, and also some symptoms, try to generate a question to display what gender that John possibly is as well as the age group.  
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/var/www/ailab/WWW/wiki/data/pages/public/t-720-atai/atai-19/final_project.txt · Last modified: 2019/10/28 20:03 by thorisson