An appreciation of John Pollock's work on the computational study of argument

Abstract

) was an influential American philosopher who made important contributions to various fields, including epistemology and cognitive science. In the last 25 years of his life, he also contributed to the computational study of defeasible reasoning and practical cognition in artificial intelligence. He developed one of the first formal systems for argumentation-based inference and he put many issues on the research agenda that are still relevant for the argumentation community today. This paper presents an appreciation of Pollock's work on defeasible reasoning and its relevance for the computational study of argument. In our opinion, Pollock deserves to be remembered as one of the founding fathers of the field of computational argument, while, moreover, his work contains important lessons for current research in this field, reminding us of the richness of its object of study.

Assessing the epistemological relevance of Dung-style argumentation theories

“…. ] resolve conflicts of opinion between intelligent agents" (p. 361) and that, moreover, its "[argumentative] characterisations of inference encapsulate the dynamic and dialectical processes of reasoning familiar in everyday debate 19 See also [42]. 20 So, [43], for example, seem to assume that AFs analyze argumentation which starts from a "joint basis of discussion" (p. 221).…”

Opening up Minds with Argumentative Dialogues

“…These Wikipedia-based datasets have later been utilised to build knowledgeable dialogue agents (Li et al, 2019;Lian et al, 2019;Zhao et al, 2020b,a;Shuster et al, 2021a). Nonetheless, using arguments as a knowledge-base for dialogue agents has received less attention, with exception of, for example, Prakken et al (2020), who developed a chatbot to persuade participants to accept that university fees should remain the same by selecting arguments from an argument graph using cosine similarity.…”

“…Typically, these agents engage in conversations with people with the aim of changing their opinions on a topic or winning debates. Accordingly, success of argumentative dialogue agents has been measured by their ability to convince people to take an action such as donating to a charity Shi et al, 2020), change their position on the subject of discussion (Tan et al, 2016;Prakken et al, 2020), or attract more votes by the audience listening to their debates (Zhang et al, 2016;Slonim et al, 2021). Other work has studied argumentation with P: I feel like pushing your kids to not eat meat or dairy products is a bit too much, other than that I really don't see a problem if it's someones choice to not eat meat or dairy products.…”