Solving stochastic optimization problems under partial observability, where one needs to adaptively make decisions with uncertain outcomes, is a fundamental but notoriously diffic...
The perceptron (also referred to as McCulloch-Pitts neuron, or linear threshold gate) is commonly used as a simplified model for the discrimination and learning capability of a bi...
An important characteristic of ubiquitous computing is that the computational services in our environment are envisioned to be far more interconnectable than today. This means it ...
Individual learning capabilities can vary from gifted to exceptionally slow; some students may take longer to understand a concept and may not be able to achieve the expected stan...
Understanding conceptual change is an important problem in modeling human cognition and in making integrated AI systems that can learn autonomously. This paper describes a model o...