Evaluating Agent Interactions Through Episodic Knowledge Graphs
Artificial Intelligence
2022-09-27 v2
Abstract
We present a new method based on episodic Knowledge Graphs (eKGs) for evaluating (multimodal) conversational agents in open domains. This graph is generated by interpreting raw signals during conversation and is able to capture the accumulation of knowledge over time. We apply structural and semantic analysis of the resulting graphs and translate the properties into qualitative measures. We compare these measures with existing automatic and manual evaluation metrics commonly used for conversational agents. Our results show that our Knowledge-Graph-based evaluation provides more qualitative insights into interaction and the agent's behavior.
Cite
@article{arxiv.2209.11746,
title = {Evaluating Agent Interactions Through Episodic Knowledge Graphs},
author = {Selene Báez Santamaría and Piek Vossen and Thomas Baier},
journal= {arXiv preprint arXiv:2209.11746},
year = {2022}
}
Comments
Accepted to 1st Workshop on Customized Chat Grounding Persona and Knowledge, at COLING (2022)