90 citations · 153 across the 12 of their papers we have counts for
16 papers · 1 filter
Learning First-Order Representations for Planning from Black-Box States: New Results
Ivan D. Rodriguez, Blai Bonet, Javier Romero +1
Recently Bonet and Geffner have shown that first-order representations for planning domains can be learned from the structure of the state space without any prior knowledge about t…
Expressing and Exploiting the Common Subgoal Structure of Classical Planning Domains Using Sketches: Extended Version
Dominik Drexler, Jendrik Seipp, Hector Geffner
Width-based planning methods deal with conjunctive goals by decomposing problems into subproblems of low width. Algorithms like SIW thus fail when the goal is not easily serializab…
Learning General Policies from Small Examples Without Supervision
Guillem Francès, Blai Bonet, Hector Geffner
Generalized planning is concerned with the computation of general policies that solve multiple instances of a planning domain all at once. It has been recently shown that these pol…
General Policies, Serializations, and Planning Width
Blai Bonet, Hector Geffner
It has been observed that in many of the benchmark planning domains, atomic goals can be reached with a simple polynomial exploration procedure, called IW, that runs in time expone…
Qualitative Numeric Planning: Reductions and Complexity
Blai Bonet, Hector Geffner
Qualitative numerical planning is classical planning extended with non-negative real variables that can be increased or decreased "qualitatively", i.e., by positive indeterminate a…
Factored Probabilistic Belief Tracking
Blai Bonet, Hector Geffner
The problem of belief tracking in the presence of stochastic actions and observations is pervasive and yet computationally intractable. In this work we show however that probabilis…