It is critical for designers of language-capable robots to enable some degree of moral
competence in those robots. This is especially critical at this point in history due to the …

Robots designed to interact with humans in realistic environments must be able to handle
uncertainty with respect to the identities and properties of the people, places, and things …

Abstract Answer Set Programming (ASP) is a declarative knowledge representation
language that uses a non-monotonic reasoning mechanism to search for all answer sets or …

We present a new system S for handling uncertainty in a quantified modal logic (first-order
modal logic). The system is based on both probability theory and proof theory. The system is …

This paper briefly surveys several prominent modeling approaches to knowledge-based
intelligent systems (KBIS) design and, especially, expert systems and the breakthroughs that …

This work considers a target tracking problem where the observed information is in the form
of natural language-type statements. More specifically, the focus is on a spatio-temporal …

Numerous applications rely on implication rules either as models of causal relations among
data, or as components of their reasoning and inference systems. Although mature and …

First order logic lies at the core of many methods in mathematics, philosophy, linguistics, and
computer science. Although important efforts have been made to extend first order logic to …

Abstract Understanding Indirect Speech Acts (ISAs) is an integral function of human
understanding of natural language. Recent attempts at understanding ISAs have used rule …

In many application scenarios such as target tracking, one is confronted with the problem of
suitably fusing both hard data (eg, radar, acoustic) and soft data (eg, text from blogs, or …