Browsing by Author "Geffner, Héctor"

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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 ...
  • Artificial Intelligence: From programs to solvers
    Geffner, Héctor (IOS Press, 2014)
    Artificial Intelligence is a brain child of Alan Turing and his universal programmable computer. During the 1960s and 1970s, AI researchers used computers for exploring intuitions about intelligence and for writing programs ...
  • Belief tracking for multi-agent planning
    Kominis, Filippos (Universitat Pompeu Fabra, 2017-12-05)
    Classical planning is the problem of finding a sequence of actions that achieve a desired goal from an initial state, assuming deterministic actions. Dynamic epistemic logic (DEL) on the other hand, provides formal frameworks ...
  • Branching and pruning: an optimal temporal POCL planner based on constraint programming
    Vidal, Vincent; Geffner, Héctor (Elsevier, 2006)
    A key feature of modern optimal planners such as graphplan and blackbox is their ability to prune large parts of the search space. Previous Partial Order Causal Link (POCL) planners provide an alternative branching scheme ...
  • Combined task and motion planning as classical AI planning
    Ferrer Mestres, Jonathan (Universitat Pompeu Fabra, 2018-05-17)
    Planning in robotics is often split into task and motion planning. The task planner decides what needs to be done, while the motion planner fills up geometric details. However, such a decomposition is not effective in general ...
  • Computing infinite plans for LTL goals using a classical planner
    Patrizini, Fabio; Lipovetzky, Nir; Giacomo, Giuseppe de; Geffner, Héctor (Association for the Advancement of Artificial Intelligence (AAAI), 2011)
    Classical planning has been notably successful in synthesizing finite plans to achieve states where propositional goals hold. In the last few years, classical planning has also been extended to incorporate temporally ...
  • Effective planning with expressive languages
    Francès, Guillem (Universitat Pompeu Fabra, 2017-11-14)
    Classical planning is concerned with finding sequences of actions that achieve a certain goal from an initial state of the world, assuming that actions are deterministic, states are fully known, and both are described in ...
  • Expressing and exploiting the common subgoal structure of classical planning domains using sketches
    Drexler, Dominik; Seipp, Jendrik; Geffner, Héctor (IJCAI Proceedings, 2021)
    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 serializable in this way or when some of the subproblems ...
  • 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 ...
  • Goal recognition over POMDPs: inferring the intention of a POMDP agent
    Ramírez Jávega, Miquel; Geffner, Héctor (Association for the Advancement of Artificial Intelligence (AAAI), 2011)
    Plan recognition is the problem of inferring the goals and plans of an agent from partial observations of her behavior. Recently, it has been shown that the problem can be formulated and solved using/nplanners, reducing ...
  • Heuristic search for generalized stochastic shortest path MDPs
    Kolobov, Andrey; Mausam; Weld, Daniel S.; Geffner, Héctor (Association for the Advancement of Artificial Intelligence (AAAI), 2011)
    Research in efficient methods for solving infinite-horizon MDPs has so far concentrated primarily on discounted MDPs and the more general stochastic shortest path problems (SSPs). These are MDPs with 1) an optimal value ...
  • 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 ...
  • New Heuristics for Planning with Action Costs
    Keyder, Emil Ragip (Universitat Pompeu Fabra, 2011-04-12)
    Classical planning is the problem of nding a sequence of actions that take an agent from an initial state to a desired goal situation, assuming deter- ministic outcomes for actions and perfect information. Satis cing ...
  • Plan recognition as planning
    Ramírez Jávega, Miquel (Universitat Pompeu Fabra, 2012-07-09)
    Plan recognition is the problem of inferring the goals and plans of an agent after partially observing its behavior. This is the inverse of planning, the problem of finding the actions that need to be done in order to ...
  • 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 ...

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