We propose a new approach to reinforcement learning which combines least squares function approximation with policy iteration. Our method is model-free and completely off policy. ...
This paper presents a lens system design algorithm using the covariance matrix adaptation evolution strategy (CMA-ES), which is one of the most powerful self-adaptation mechanisms....
We consider bargaining problems under the assumption that players are loss averse, i.e., experience disutility from obtaining an outcome lower than some reference point. We follow...
Abstract—Verification of application requirements is becoming a bottleneck in system-on-chip design, as the number of applications grows. Traditionally, the verification comple...
Databases are often incomplete because of the presence of disjunctive information, due to con icts, partial knowledge and other reasons. Queries against such databases often ask q...