# Implementing Argumentation-enabled Empathic Agents

## TL;DR

This paper develops prototypes of empathic agents using argumentation theory within multi-agent systems, focusing on resolving belief inconsistencies through admissible set-based semantics, especially the maximal ideal extension.

## Contribution

It extends previous empathic agent concepts by integrating argumentation theory to handle belief conflicts, identifying the maximal ideal extension as the most suitable semantics.

## Key findings

- Maximal ideal extension is most feasible for resolving belief inconsistencies.
- Prototypes demonstrate practical implementation of argumentation in empathic agents.
- Analysis confirms the effectiveness of admissible set-based semantics in multi-agent belief reconciliation.

## Abstract

In a previous publication, we introduced the core concepts of empathic agents as agents that use a combination of utility-based and rule-based approaches to resolve conflicts when interacting with other agents in their environment. In this work, we implement proof-of-concept prototypes of empathic agents with the multi-agent systems development framework Jason and apply argumentation theory to extend the previously introduced concepts to account for inconsistencies between the beliefs of different agents. We then analyze the feasibility of different admissible set-based argumentation semantics to resolve these inconsistencies. As a result of the analysis we identify the maximal ideal extension as the most feasible argumentation semantics for the problem in focus.