Numerous formalisms and dedicated algorithms have been designed in the last decades to model and solve decision making problems. Some formalisms, such as constraint networks, can ...
Several formalisms exist to express and solve decision problems. Each is designed to capture different kinds of knowledge: utilities expressing preferences, uncertainties on the en...
Accurate knowledge of the effect of parameter uncertainty on process design and operation is essential for optimal and feasible operation of a process plant. Existing approaches de...
This paper proposes a new planning architecture for agents operating in uncertain and dynamic environments. Decisiontheoretic planning has been recognized as a useful tool for rea...
Partially Observable Markov Decision Process (POMDP) is a popular framework for planning under uncertainty in partially observable domains. Yet, the POMDP model is riskneutral in ...