Techniques for plan recognition under uncertainty require a stochastic model of the plangeneration process. We introduce probabilistic state-dependent grammars (PSDGs) to represen...
Weshowthat by inferring parametexdomainsof planningoperators,given the definitions of the operators and the initial and goal conditions, we can often speed up the planning process...
An intelligent problem solver must be able to decompose a complex problem into simpler parts. A decomposition algorithm would not only be bene cial for traditional subgoal-oriente...
We propose an online algorithm for planning under uncertainty in multi-agent settings modeled as DEC-POMDPs. The algorithm helps overcome the high computational complexity of solv...
Abstract. We consider a fundamental problem, called QoS-aware Multicommodity Flow, for assessing robustness in transportation planning. It constitutes a natural generalization of t...