: Indefinite probabilities are a novel technique for quantifying uncertainty, which were created as part of the PLN (Probabilistic Logic Networks) logical inference engine, which i...
Kernel Ridge Regression (KRR) and the recently developed Kernel Aggregating Algorithm for Regression (KAAR) are regression methods based on Least Squares. KAAR has theoretical adv...
Steven Busuttil, Yuri Kalnishkan, Alexander Gammer...
Representing uncertainty and reasoning with dynamically evolving systems are two related issues that are in the heart of many information systems. In this paper we show that these ...
Rich computer simulations or quantitative models can enable an agent to realistically predict real-world behavior with precision and performance that is difficult to emulate in log...
Cognitive architectures play a vital role in providing blueprints for building future intelligent systems supporting a broad range of capabilities similar to those of humans. How u...
Wlodzislaw Duch, Richard Jayadi Oentaryo, Michel P...
One might imagine that AI systems with harmless goals will be harmless. This paper instead shows that intelligent systems will need to be carefully designed to prevent them from be...
One approach in pursuit of general intelligent agents has been to concentrate on the underlying cognitive architecture, of which Soar is a prime example. In the past, Soar has reli...
Learning theory and programs to date are inductively bounded: they can be described as "wind-up toys" which can only learn the kinds of things that their designers envisi...
There are a wide variety of approaches to Artificial Intelligence. Yet interestingly we find that these can all be grouped into four broad categories: Silver Bullets, Core Values, ...