This paper proposes an approach to mixed environment training of manual tasks requiring concurrent use of psychomotor and cognitive skills. To train concurrent use of both skill s...
Aaron Kotranza, D. Scott Lind, Carla M. Pugh, Benj...
Two of the most commonly used models in computational learning theory are the distribution-free model in which examples are chosen from a fixed but arbitrary distribution, and the ...
In this paper we embed evolutionary computation into statistical learning theory. First, we outline the connection between large margin optimization and statistical learning and s...
With the goal to generate more scalable algorithms with higher efficiency and fewer open parameters, reinforcement learning (RL) has recently moved towards combining classical tec...
An important goal for the generative and developmental systems (GDS) community is to show that GDS approaches can compete with more mainstream approaches in machine learning (ML)....