A robot must often react to events in its environment and exceptional conditions by suspendingor abandoning its current plan and selecting a new plan that is an appropriate respons...
We describe a novel integration of Planning with Probabilistic State Estimation and Execution resulting in a unified representational and computational framework based on declarat...
Conor McGann, Frederic Py, Kanna Rajan, John Ryan,...
In model-based control, a planner uses a system description to create a plan that achieves production goals. The same model can be used by model-based diagnosis to indirectly infe...
Lukas Kuhn, Bob Price, Minh Binh Do, Juan Liu, Ron...
Set-valued estimation offers a way to account for imprecise knowledge of the prior distribution of a Bayesian statistical inference problem. The set-valued Kalman filter, which p...
While John Holland has always envisioned learning classifier systems (LCSs) as cognitive systems, most work on LCSs has focused on classification, datamining, and function appro...