Entertainment animatronics has traditionally been a discipline devoid of interactivity. Previously, we brought interactivity to this field by creating a suite of content authoring...
Seema Patel, William Bosley, David Culyba, Sabrina...
Reinforcement learning is an effective machine learning paradigm in domains represented by compact and discrete state-action spaces. In high-dimensional and continuous domains, ti...
Supply chains are ubiquitous in the manufacturing of many complex products. Traditionally, supply chains have been created through the intricate interactions of human representati...
Policy Reuse is a method to improve reinforcement learning with the ability to solve multiple tasks by building upon past problem solving experience, as accumulated in a Policy Li...
Mixed-Initiative approaches to Planning and Scheduling are being applied in different real world domains. While several recent successful examples of such tools encourage a wider ...