On the Relationship Between KR Approaches for Explainable Planning

In this paper, we build upon notions from knowledge representation and reasoning (KR) to expand a preliminary logic-based framework that characterizes the model reconciliation problem for explainable planning. We also provide a detailed exposition on the relationship between similar KR techniques, such as abductive explanations and belief change, and their applicability to explainable planning.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
02/26/2020

The Emerging Landscape of Explainable AI Planning and Decision Making

In this paper, we provide a comprehensive outline of the different threa...
research
10/15/2022

ProtoVAE: A Trustworthy Self-Explainable Prototypical Variational Model

The need for interpretable models has fostered the development of self-e...
research
08/14/2019

Towards Explainable AI Planning as a Service

Explainable AI is an important area of research within which Explainable...
research
06/14/2022

Explainable AI for High Energy Physics

Neural Networks are ubiquitous in high energy physics research. However,...
research
03/19/2019

Why Couldn't You do that? Explaining Unsolvability of Classical Planning Problems in the Presence of Plan Advice

Explainable planning is widely accepted as a prerequisite for autonomous...
research
10/02/2017

What Does Explainable AI Really Mean? A New Conceptualization of Perspectives

We characterize three notions of explainable AI that cut across research...
research
03/27/2021

Local Explanations via Necessity and Sufficiency: Unifying Theory and Practice

Necessity and sufficiency are the building blocks of all successful expl...

Please sign up or login with your details

Forgot password? Click here to reset