Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
Fundamental concepts of qualitative probabilistic networks
Artificial Intelligence
Formulation of tradeoffs in planning under uncertainty
Formulation of tradeoffs in planning under uncertainty
Robot's Dilemma: The Frame Problem in Artificial Intelligence
Robot's Dilemma: The Frame Problem in Artificial Intelligence
STRIPS: a new approach to the application of theorem proving to problem solving
IJCAI'71 Proceedings of the 2nd international joint conference on Artificial intelligence
A model for projection and action
IJCAI'89 Proceedings of the 11th international joint conference on Artificial intelligence - Volume 2
Accounting for context in plan recognition, with application to traffic monitoring
UAI'95 Proceedings of the Eleventh conference on Uncertainty in artificial intelligence
A structured, probabilistic representation of action
UAI'94 Proceedings of the Tenth international conference on Uncertainty in artificial intelligence
Constructing belief networks to evaluate plans
UAI'94 Proceedings of the Tenth international conference on Uncertainty in artificial intelligence
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The virtue of the STRIPS assumption for planning is that it bounds the information relevant to determining the effects of actions. Viewing the "assumption" as a statement about beliefs, we find that it does not actually assume anything about the world itself. We can characterize the assertion about beliefs in terms of probabilistic independence, thereby facilitating analysis of representations for planning under uncertainty. This interpretation separates the STRIPS assumption from other necessary features of a planning architecture, such as its model of persistence and its inferential policies. By isolating these factors, we can understand the role of dependence across a wide range of planners and action representations. Graphical models of dependence developed for probabilistic analysis provide a convenient tool for verifying the STRIPS assumption for a variety of planning systems. Investigation of a few representative systems reveals a Markovian event structure common to these planning models.