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 ...
Business processes used in networked business are often large and complex, which makes them difficult to manage and change. In this paper we address this lack of flexibility by pr...
Tim van Eijndhoven, Maria-Eugenia Iacob, Mar&iacut...
In this paper, it will be shown that it is feasible to extract finite state machines in a domain of, for rule extraction, previously unencountered complexity. The algorithm used i...
Objective Healthcare organizations must de-identify patient records before sharing data. Many organizations rely on the Safe Harbor Standard of the HIPAAPrivacy Rule, which enumer...
The paper presents a pattern-oriented agent-based model to simulate the dynamics of a stock market. The model generates satisfactory market macro-level trend and volatility while t...