The search for finite-state controllers for partially observable Markov decision processes (POMDPs) is often based on approaches like gradient ascent, attractive because of their ...
We describe a new algorithm for proving temporal properties expressed in LTL of infinite-state programs. Our approach takes advantage of the fact that LTL properties can often be...
This work proposes to learn visual encodings of attention patterns that enables sequential attention for object detection in real world environments. The system embeds a saccadic d...
Decision procedures have long been a fixture in program analysis, and reasoning about string constraints is a key element in many program analyses and testing frameworks. Recent ...
We consider the problem of actively learning the mean values of distributions associated with a finite number of options. The decision maker can select which option to generate t...