As our business, academic, and personal lives continue to move at an ever-faster pace, finding times for busy people to meet has become an art. One of the most perplexing challeng...
Mike Brzozowski, Kendra Carattini, Scott R. Klemme...
Current approaches to explicit user modelling are generally time consuming and tedious for the user. Oftentimes poor usability and overly long questionnaires deter the end user fro...
We present the first design for a fully expressive iterative combinatorial exchange (ICE). The exchange incorporates a tree-based bidding language that is concise and expressive ...
David C. Parkes, Ruggiero Cavallo, Nick Elprin, Ad...
We present the design and analysis of the first fully expressive, iterative combinatorial exchange (ICE). The exchange incorporates a tree-based bidding language (TBBL) that is co...
Benjamin Lubin, Adam I. Juda, Ruggiero Cavallo, S&...
We generalise the problem of inverse reinforcement learning to multiple tasks, from multiple demonstrations. Each one may represent one expert trying to solve a different task, or ...