An Argumentation-based Approach for Explaining Goal Selection in
  Intelligent Agents
  During the first step of practical reasoning, i.e. deliberation or goals
selection, an intelligent agent generates a set of pursuable goals and then
selects which of them he commits to achieve. Explainable Artificial
Intelligence (XAI) systems, including intelligent agents, must be able to
explain their internal decisions. In the context of goals selection, agents
should be able to explain the reasoning path that leads them to select (or not)
a certain goal. In this article, we use an argumentation-based approach for
generating explanations about that reasoning path. Besides, we aim to enrich
the explanations with information about emerging conflicts during the selection
process and how such conflicts were resolved. We propose two types of
explanations: the partial one and the complete one and a set of explanatory
schemes to generate pseudo-natural explanations. Finally, we apply our proposal
to the cleaner world scenario.
