Reinforcement learning problems are commonly tackled with temporal difference methods, which use dynamic programming and statistical sampling to estimate the long-term value of ta...
The challenge we address is to reason about projected resource usage within a hierarchical task execution framework in order to improve agent effectiveness. Specifically, we seek ...
The General Game Playing (GGP) problem is concerned with developing systems capable of playing many different games, even games the system has never encountered before. Successful...
Exploratory testing (ET) – simultaneous learning, test design, and test execution – is an applied practice in industry but lacks research. We present the current knowledge of ...
The representation used by a learning algorithm introduces a bias which is more or less well-suited to any given learning problem. It is well known that, across all possible probl...