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This paper reviews studies that combine machine learning (ML) with argumentation, a way to use logic and reasoning to make decisions. The authors found two main ways that these fields are being combined. The first is using argumentation to improve or explain ML models. For example, researchers are using argumentation to help ML models make better predictions, especially when the data is complex or has exceptions. Argumentation is also being used to explain how ML models make their decisions, which is important for building trust and understanding how these models work. The second way is using ML to support argumentation. For example, ML is being used to automatically build argumentation frameworks, which are sets of arguments and their relationships. This can be helpful because building these frameworks by hand can be time-consuming and difficult. Researchers are also using ML to predict which arguments are likely to be accepted in an argumentation framework, which can help speed up decision-making.
This paper reviews studies that combine machine learning (ML) with argumentation, a way to use logic and reasoning to make decisions. The authors found two main ways that these fields are being combined. The first is using argumentation to improve or explain ML models. For example, researchers are using argumentation to help ML models make better predictions, especially when the data is complex or has exceptions. Argumentation is also being used to explain how ML models make their decisions, which is important for building trust and understanding how these models work. The second way is using ML to support argumentation. For example, ML is being used to automatically build argumentation frameworks, which are sets of arguments and their relationships. This can be helpful because building these frameworks by hand can be time-consuming and difficult. Researchers are also using ML to predict which arguments are likely to be accepted in an argumentation framework, which can help speed up decision-making.