This paper contributes to solve effectively stochastic resource allocation problems known to be NP-Complete. To address this complex resource management problem, the merging of tw...
When human-multiagent teams act in real-time uncertain domains, adjustable autonomy (dynamic transferring of decisions between human and agents) raises three key challenges. First...
Model-based Bayesian reinforcement learning has generated significant interest in the AI community as it provides an elegant solution to the optimal exploration-exploitation trade...
For newly designed or transformed business processes, accurately predicting business performances such as costs and customer services before actual deployment is very important. W...
Markov Decision Processes (MDPs), currently a popular method for modeling and solving decision theoretic planning problems, are limited by the Markovian assumption: rewards and dy...