Models for sequential decision making under uncertainty (e.g., Markov decision processes,or MDPs) have beenstudied in operations research for decades. The recent incorporation of ...
We present an efficient method for learning part-based object class models from unsegmented images represented as sets of salient features. A model includes parts' appearance...
Reinforcement Learning (RL) is the study of programs that improve their performance by receiving rewards and punishments from the environment. Most RL methods optimize the discoun...
This paper represents a description of our approach to the problem of topological localization of a mobile robot using visual information. Our method has been developed for ImageCL...
Background: Due to their role of receptors or transporters, membrane proteins play a key role in many important biological functions. In our work we used Grammatical Inference (GI...