most citedA New Model of Plan Recognition

119 citations · 171 across the 6 of their papers we have counts for

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cs.AI2020

Provenance-Based Assessment of Plans in Context

Scott E. Friedman, Robert P. Goldman, Richard G. Freedman +3

Many real-world planning domains involve diverse information sources, external entities, and variable-reliability agents, all of which may impact the confidence, risk, and sensitiv…

cs.AI20131 cited

Plan Recognition in Stories and in Life

Eugene Charniak, Robert P. Goldman

Plan recognition does not work the same way in stories and in "real life" (people tend to jump to conclusions more in stories). We present a theory of this, for the particular case…

cs.AI201351 cited

Dynamic Construction of Belief Networks

Robert P. Goldman, Eugene Charniak

We describe a method for incrementally constructing belief networks. We have developed a network-construction language similar to a forward-chaining language using data dependencie…

cs.AI2013

Integrating Model Construction and Evaluation

Robert P. Goldman, John S. Breese

To date, most probabilistic reasoning systems have relied on a fixed belief network constructed at design time. The network is used by an application program as a representation of…

cs.AI2013

Epsilon-Safe Planning

Robert P. Goldman, Mark S. Boddy

We introduce an approach to high-level conditional planning we call epsilon-safe planning. This probabilistic approach commits us to planning to meet some specified goal with a pro…

cs.AI2013119 cited

A New Model of Plan Recognition

Robert P. Goldman, Christopher W. Geib, Christopher A. Miller

We present a new abductive, probabilistic theory of plan recognition. This model differs from previous plan recognition theories in being centered around a model of plan execution:…