Partially observable Markov decision processes (POMDPs) are an intuitive and general way to model sequential decision making problems under uncertainty. Unfortunately, even approx...
Tao Wang, Pascal Poupart, Michael H. Bowling, Dale...
The need to improve a suboptimal execution plan picked by the query optimizer for a repeatedly run SQL query arises routinely. Complex expressions, skewed or correlated data, and ...
— We concern ourselves with the process of making optimized production planning decisions in the face of low frequency, high impact uncertainty, which takes the form of a small n...
This paper proposes a comprehensive model for test planning in a core-based environment. The main contribution of this work is the use of several types of TAMs and the considerati...
The present article proposes a novel computational approach to the motor planning. In this approach, each motor command is represented as a linear combination of prefixed basis p...