Decentralized Markov Decision Processes (DEC-MDPs) are a popular model of agent-coordination problems in domains with uncertainty and time constraints but very difficult to solve...
This paper presents a new approach to integrated security and dependability evaluation, which is based on stochastic modeling techniques. Our proposal aims to provide operational m...
Karin Sallhammar, Bjarne E. Helvik, Svein J. Knaps...
—For software, the costs of failures are not clearly understood. Often, these costs disappear in the costs of testing, the general developments costs, or the operating expenses. ...
Abstract. Many reinforcement learning domains are highly relational. While traditional temporal-difference methods can be applied to these domains, they are limited in their capaci...
Trevor Walker, Lisa Torrey, Jude W. Shavlik, Richa...
Learning agents, whether natural or artificial, must update their internal parameters in order to improve their behavior over time. In reinforcement learning, this plasticity is ...