Humans understand language by extracting information (meaning) from sentences,
combining it with existing commonsense knowledge, and then performing reasoning to draw …

We present the AutoConcierge system that can “understand” human dialogs in a specific
domain, namely, restaurant recommendation. AutoConcierge will interactively “understand” …

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 …

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 …

The use of assurance cases is gaining popularity, particularly in the safety-critical system
industry, as an organized approach to submitting documentation for the safety and security …

Text-based games (TBGs) have emerged as an important collection of NLP tasks, requiring
reinforcement learning (RL) agents to combine natural language understanding with …

Explainable artificial intelligence (XAI) aims at addressing complex problems by coupling
solutions with reasons that justify the provided answer. In the context of Answer Set …

Assurance cases offer a structured way to present arguments and evidence for certification
of systems where safety and security are critical. However, creating and evaluating these …

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 …