WΓ€hle die Region, die am besten zu deinem Standort oder deinen Vorlieben passt. WΓ€hlen Sie Ihre bevorzugte Sprache fΓΌr das beste Surferlebnis. WΓ€hle die Sprachen fΓΌr Stellenanzeigen, die du sehen mΓΆchtest. Diese Einstellung bestimmt, welche Stellenanzeigen dir angezeigt werden. Chatbots have come along way from Clippy, the much-maligned paperclip-shaped Microsoft Office chatbot of the late 90s and early 00s.
But what if they could? Researchers at the Centre for Artificial Intelligence Research CAIR at the University of Agder are developing a chatbot that will help young people struggling with social health problems such as social isolation, anxiety, eating disorders, depression, and self harm.
Raheleh Jafari, a postdoctoral researcher from Iran, is one of the CAIR researchers working on the chatbot. She is an expert in fuzzy logic, a type of mathematical model that can be used to help the chatbot think more like a person would. At the University of Agder, she uses her expertise to generate the data that is used to train the chatbot to accurately answer questions. To teach the bot how to respond, Raheleh and her coworkers started by generating thousands of potential questions and answers.
This is where fuzzy logic comes in. Rather than come up with every, single potential question and answer that the chatbot might need to carry out a conversation, Raheleh uses fuzzy logic to get the chatbot to think more like a real person.
Computers are programmed to perceive things as either true or false. In the case of the chatbot, this means that if you give it a data set of 2, possible answers, the bot can apply fuzzy logic to expand the data to over 10, possible answers.
