—We introduce a new BDD-like data structure called Hybrid-Restriction Diagrams (HRDs) for the representation and manipulation of linear hybrid automata (LHA) state-spaces and pre...
A central problem in artificial intelligence is to choose actions to maximize reward in a partially observable, uncertain environment. To do so, we must learn an accurate model of ...
Partially-observable Markov decision processes (POMDPs) provide a powerful model for sequential decision-making problems with partially-observed state and are known to have (appro...
This study focuses on the development of a conceptual simulation modeling tool that can be used to structure a domain specific simulation environment. The issues in Software Engin...
The method of stochastic state classes approaches the analysis of Generalised Semi Markov Processes (GSMP) through symbolic derivation of probability density functions over Differe...