The linear model with sparsity-favouring prior on the coefficients has important applications in many different domains. In machine learning, most methods to date search for maxim...
In many AI settings an agent is comprised of both actionplanning and action-execution components. We examine the relationship between the precision of the execution component, the...
ys when planning meant searching for a sequence of abstract actions that satisfied some symbolic predicate. Robots can now learn their own representations through statistical infe...
We are working on a project aimed at building next generation analyst support tools that focus analysts’ attention on the most critical and novel information found within the da...
Because of privacy concerns, agents may not want to reveal information that could be of use in problem solving. As a result, there are potentially important tradeoffs between main...