Markov decision processes (MDPs) and stochastic control constitute pivotal frameworks for modelling decision-making in systems subject to uncertainty. At their core, MDPs provide a structured means to ...

This paper examines monotonicity results for a fairly general class of partially observable Markov decision processes. When there are only two actual states in the system and when the actions taken ...

We consider Markov decision processes with unknown transition probabilities and unknown single-period expected cost functions, and we study a method for estimating these quantities from historical or ...

Quantum cognition applies principles derived from quantum theory to elucidate the non-classical probabilistic aspects of decision making. This interdisciplinary field challenges conventional, ...