POMDPs are the models of choice for reinforcement learning (RL) tasks where the environment cannot be observed directly. In many applications we need to learn the POMDP structure ...
Abstract. This paper introduces the notion of finite precision timed automata (FPTAs) and proposes a data structure to represent its symbolic states. To reduce the state space, FP...
Abstract. We present a reflection on the evolution of the different methods for constructing minimal deterministic acyclic finite-state automata from a finite set of words. We ...
In Description Logics (DLs), both tableau-based and automata-based algorithms are frequently used to show decidability and complexity results for basic inference problems such as c...
This paper introduces a Cellular Automata (CA) approach to spatiotemporal data mining (STDM). The recently increasing interest in using Genetic Algorithms and other evolutionary te...