Understanding the meaning of a text is a fundamental challenge of natural language understanding (NLU) research. An ideal NLU system should process a language in a way …
Driving an automobile involves the tasks of observing surroundings, then making a driving decision based on these observations (steer, brake, coast, etc.). In autonomous driving, all …
Automated legal reasoning and its application in smart contracts and automated decisions are increasingly attracting interest. In this context, ethical and legal concerns make it …
We present the AutoConcierge system that can “understand” human dialogs in a specific domain, namely, restaurant recommendation. AutoConcierge will interactively “understand” …
FOLD-RM is an automated inductive learning algorithm for learning default rules for mixed (numerical and categorical) data. It generates an (explainable) answer set programming …
H Wang, G Gupta - International Symposium on Functional and Logic …, 2022 - Springer
FOLD-R is an automated inductive learning algorithm for learning default rules for mixed (numerical and categorical) data. It generates an (explainable) normal logic program (NLP) …
J Morris - … of the Eighteenth International Conference on Artificial …, 2021 - dl.acm.org
" Rules as Code" in this paper is used to refer to a proposed methodology of legislative and regulatory drafting. 1 That legislation can be represented in declarative code for automation …
Text-based games (TBGs) have emerged as an important collection of NLP tasks, requiring reinforcement learning (RL) agents to combine natural language understanding with …
In this paper, we present a system, called xASP, for generating explanations that explain why an atom belongs to (or does not belong to) an answer set of a given program. The …