• Domain dependent heuristics and tie breakers : topics in automated planning 

      Corrêa, Augusto Blaas (2018) [Trabalho de conclusão de graduação]
      Automated planning is an important general problem solving technique in Artificial Intelligence (AI). In planning, given a initial state of the world, a goal and a set of actions, we want to find a sequence of these actions ...
    • Learning deadlocks in sokoban 

      Boelter, Jean Persi (2018) [Trabalho de conclusão de graduação]
      In this thesis, we present an approach for deadlock detection in Sokoban based on neural networks. Sokoban is a challenging state space problem in artificial intelligence due to many characteristics, being the presence of ...
    • A new greedy algorithm to estimate the Post-hoc method 

      Avila, Henry Bernardo Kochenborger de (2024) [Trabalho de conclusão de graduação]
      Heuristic functions estimate how far each state is from the goal condition and have been widely used to guide state-space search to solve planning tasks. Effective heuristic func tions find a good compromise between ...
    • A non-admissible heuristic function based on synchronized abstract plans 

      Duranti, Nicolas Casagrande (2023) [Trabalho de conclusão de graduação]
      Classical Planning is a traditional Artificial Intelligence problem that consists of finding a sequence of actions, called a plan, to achieve some desired goal given an initial state. We say that the plan cost is the sum ...
    • PEA∗+IDA∗ : an improved hybrid memory-restricted algorithm 

      Schwartzhaupt, Frederico Messa (2021) [Trabalho de conclusão de graduação]
      It is well-known that the search algorithms A∗ and Iterative Deepening A∗ (IDA∗ ) can fail to solve state-space tasks optimally due to time and memory limits. The former typically fails in memory-restricted scenarios and ...