This paper extends the framework of dynamic influence diagrams (DIDs) to the multi-agent setting. DIDs are computational representations of the Partially Observable Markov Decisio...
Previous work on context-specific independence in Bayesian networks is driven by a common goal, namely to represent the conditional probability tables in a most compact way. In th...
In this paper, we develop a symbolic representation for timed concurrent constraint (tccp) programs, which can be used for defining a lightweight model–checking algorithm for re...
This paper proposes a new architecture for memorybased floating-point numeric function generators (NFGs). The design method uses piecewise-split edge-valued multivalued decision ...
Abstract. This paper describes the implementation of predicate abstraction techniques to automatically compute symbolic backward reachable sets of high dimensional piecewise affine...