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Plan-Length Bounds: Beyond 1-Way Dependency
2019
PROCEEDINGS OF THE THIRTIETH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE AND THE TWENTY-EIGHTH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE
We consider the problem of compositionally computing upper bounds on lengths of plans. Following existing work, our approach is based on a decomposition of state-variable dependency graphs (a.k.a. causal graphs). Tight bounds have been demonstrated previously for problems where key dependencies flow in a single direction—i.e. manipulating variable v1 can disturb the ability to manipulate v2 and not vice versa. We develop a more general bounding approach which allows us to compute useful bounds
doi:10.1609/aaai.v33i01.33017502
fatcat:rd3sc6ingzbftaijl6ugkdziym