Reinforcement learning in real-world domains suffers from three curses of dimensionality: explosions in state and action spaces, and high stochasticity. We present approaches that ...
To be effective, an agent that collaborates with humans needs to be able to learn new tasks from humans they work with. This paper describes a system that learns executable task m...
James F. Allen, Nathanael Chambers, George Ferguso...
Adaptive Time Warp protocols in the literature are usually based on a pre-defined analytic model of the system, expressed as a closed form function that maps system state to cont...
: This work presents an original algorithmic model of some essential features of psychogenetic theory, as was proposed by J.Piaget. Specifically, we modeled some elements of cognit...
—Detecting unknown malicious code (malcode) is a challenging task. Current common solutions, such as anti-virus tools, rely heavily on prior explicit knowledge of specific instan...
Robert Moskovitch, Shay Pluderman, Ido Gus, Dima S...