We propose a new decision-theoretic approach for solving execution-time deliberation scheduling problems using recent advances in Generalized Semi-Markov Decision Processes (GSMDP...
Current turn-taking approaches for spoken dialogue systems rely on the speaker releasing the turn before the other can take it. This reliance results in restricted interactions th...
We address the volumetric reconstruction problem that takes as input a series of orthographic multi-energy x-ray images, producing as output a reconstructed model space consisting...
Sang N. Le, Mei Kay Lee, Shamima Banu, Anthony C. ...
Hierarchical reinforcement learning (RL) is a general framework which studies how to exploit the structure of actions and tasks to accelerate policy learning in large domains. Pri...
This work details an auction-based model for problem decomposition in Genetic Programming classification. The approach builds on the population-based methodology of Genetic Progra...