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 ...
The weight of a randomly chosen link in the shortest path tree on the complete graph with exponential i.i.d. link weights is studied. The corresponding exact probability generatin...
This paper presents a novel and mathematically rigorous Bayes recursion for tracking a target that generates multiple measurements with state dependent sensor field of view and clu...
The success ofreinforcement learninginpractical problems depends on the ability to combine function approximation with temporal di erence methods such as value iteration. Experime...
In some cases, minimum Sum-Of-Products (SOP) expressions of Boolean functions can be derived by detecting decomposition and observing the functional properties such as unateness, ...