Abstract--We present the STack ARchitecture (STAR) automaton. It is a fixed structure, multiaction, reward-penalty learning automaton, characterized by a star-shaped state transiti...
Finite state machines have been used to model a number of classes of system and there has thus been much interest in the automatic generation of test sequences from finite state m...
This paper presents a sequential state estimation method with arbitrary probabilistic models expressing the system’s belief. Probabilistic models can be estimated by Maximum a po...
We propose a model-based learning algorithm, the Adaptive Aggregation Algorithm (AAA), that aims to solve the online, continuous state space reinforcement learning problem in a de...
This work is devoted to the modelling of phase transition. The thermodynamic model for phase transition chosen is a model with two equations of state, each of them modelling one p...