Using Preferences over Sources of Information in Argumentation-Based Reasoning

Argumentation-based reasoning plays an important role in agent reasoning and communication, yet little research has been carried out on the issues in integrating argumentation techniques into practical multi-agent platforms and the various sources of information in such systems. In this work, we extend an argumentation-based reasoning mechanism to take into account preferences over arguments supporting contrary conclusions, which in practice means the agent will be able to act more informedly, being able to decide on beliefs about which it would be otherwise ambivalent. Such preferences come from elements that are present or can be more easily obtained in the context of practical multi-agent programming platforms, such as multiple sources from which the information (used to construct the arguments) was acquired, as well as varying degrees of trust on them. Further, we introduce different agent profiles by varying the way certain operators are applied over the various information sources leading to the preferences over competing arguments in our approach. Unlike previous approaches, our approach accounts for multiple sources for a single piece of information and is based on an argumentation-based reasoning mechanism implemented on a multi-agent platform so arguably more computationally grounded than those approaches.