Browsing by Author "Bonet, Blai"

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  • Action selection for MDPs: anytime AO* vs. UCT
    Bonet, Blai; Geffner, Héctor (Association for the Advancement of Artificial Intelligence (AAAI), 2012)
    In the presence of non-admissible heuristics, A* and other best-first algorithms can be converted into anytime optimal algorithms over OR graphs, by simply continuing the search after the first solution is found. The same ...
  • Flexible FOND planning with explicit fairness assumptions
    Rodriguez, Ivan D.; Bonet, Blai; Sardina, Sebastian; Geffner, Héctor (Association for the Advancement of Artificial Intelligence (AAAI), 2021)
    We consider the problem of reaching a propositional goal condition in fully-observable non-deterministic (FOND) planning under a general class of fairness assumptions that are given explicitly. The fairness assumptions are ...
  • FOND planning with explicit fairness assumptions
    Rodriguez, Ivan D.; Bonet, Blai; Sardina, Sebastian; Geffner, Héctor (AI Access Foundation, 2022)
    We consider the problem of reaching a propositional goal condition in fully-observable nondeterministic (FOND) planning under a general class of fairness assumptions that are given explicitly. The fairness assumptions are ...
  • General policies, representations, and planning width
    Bonet, Blai; Geffner, Héctor (Association for the Advancement of Artificial Intelligence (AAAI), 2021)
    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 exponential in the problem width. Such problems ...
  • Heuristics for planning with penalties and rewards formulated in logic and computed through circuits
    Bonet, Blai; Geffner, Héctor (Elsevier, 2008)
    The automatic derivation of heuristic functions for guiding the search for plans is a fundamental technique in planning. The type of heuristics that have been considered so far, however, deal only with simple planning ...
  • Learning first-order representations for planning from black box states: new results
    Rodriguez, Ivan D.; Bonet, Blai; Romero, Javier; Geffner, Héctor (International Joint Conferences on Artificial Intelligence Organization, 2021)
    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 the action schemas or domain predicates. ...
  • Learning general policies from small examples without supervision
    Francès, Guillem; Bonet, Blai; Geffner, Héctor (Association for the Advancement of Artificial Intelligence (AAAI), 2021)
    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 policies can be computed in two steps: first, ...
  • mGPT: a probabilistic planner based on heuristic search
    Bonet, Blai; Geffner, Héctor (Association for the Advancement of Artificial Intelligence (AAAI), 2005)
    We describe the version of the GPT planner to be used in the planning competition. This version, called mGPT, solves mdps specified in the ppddl/nlanguage by extracting and using different classes of lower bounds, along ...
  • Planning as heuristic search
    Bonet, Blai; Geffner, Héctor (Elsevier, 2001)
    In the AIPS98 Planning Contest, the hsp planner showed that heuristic search planners can be competitive with state-of-the-art Graphplan and sat planners. Heuristic search planners like hsp transform planning problems into ...
  • Planning under partial observability by classical replanning: theory and experiments
    Bonet, Blai; Geffner, Héctor (Association for the Advancement of Artificial Intelligence (AAAI), 2011)
    Planning with partial observability can be formulated as a non-deterministic search problem in belief space. The problem is harder than classical planning as keeping track of beliefs is harder than keeping track of states, ...
  • Width and complexity of belief tracking in non-deterministic conformant and contingent planning
    Bonet, Blai; Geffner, Héctor (Association for the Advancement of Artificial Intelligence, 2012)
    It has been shown recently that the complexity of belief tracking in deterministic conformant and contingent planning is exponential in a width parameter that is often bounded and small. In this work, we introduce a new ...

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