This paper studies the problem of modeling complex domains of actions and change within highlevel action description languages. We investigate two main issues of concern: (a) can ...
A fundamental problem in neural network research, as well as in many other disciplines, is finding a suitable representation of multivariate data, i.e. random vectors. For reasons...
In recent years, sparse representation originating from signal compressed sensing theory has attracted increasing interest in computer vision research community. However, to our b...
This paper focuses on an important step in the creation of a system of meaning representation and the development of semantically-annotated parallel corpora, for use in applicatio...
Bonnie J. Dorr, Rebecca J. Passonneau, David Farwe...
A key component of any reinforcement learning algorithm is the underlying representation used by the agent. While reinforcement learning (RL) agents have typically relied on hand-...