An Argumentation-based Approach for Explaining Goal Selection in Intelligent Agents

TL;DR

This paper presents an argumentation-based method for explaining goal selection in intelligent agents, providing transparent reasoning paths and conflict resolution insights to enhance explainability in AI systems.

Contribution

It introduces a novel argumentation framework for generating natural-language explanations of goal selection and conflict resolution in intelligent agents.

Findings

Effective explanation of goal selection process

Inclusion of conflict resolution details

Application to a cleaner world scenario

Abstract

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.