Abstract. We present an implementation of model-based online reinforcement learning (RL) for continuous domains with deterministic transitions that is specifically designed to achi...
Model-based diagnostic reasoning often leads to a large number of diagnostic hypotheses. The set of diagnoses can be reduced by taking into account extra observations (passive mon...
Alexander Feldman, Gregory M. Provan, Arjan J. C. ...
Abstract— Robustness and reliability are critical issues in network management. To provide resiliency, a popular protection scheme against network failures is the simultaneous ro...
In this paper, we consider the problem of designing incentive compatible auctions for multiple (homogeneous) units of a good, when bidders have private valuations and private budg...
Sayan Bhattacharya, Vincent Conitzer, Kamesh Munag...
In transfer learning the aim is to solve new learning tasks using fewer examples by using information gained from solving related tasks. Existing transfer learning methods have be...