2 citations · 2 across the 3 of their papers we have counts for
4 papers · 1 filter
Understanding Sample Generation Strategies for Learning Heuristic Functions in Classical Planning
R. V. Bettker, P. P. Minini, A. G. Pereira +1
We study the problem of learning good heuristic functions for classical planning tasks with neural networks based on samples represented by states with their cost-to-goal estimates…
Iterative Depth-First Search for Fully Observable Non-Deterministic Planning
Ramon Fraga Pereira, André G. Pereira, Frederico Messa +1
Fully Observable Non-Deterministic (FOND) planning models uncertainty through actions with non-deterministic effects. Existing FOND planning algorithms are effective and employ a w…
Procedural Generation of Initial States of Sokoban
Dâmaris S. Bento, André G. Pereira, Levi H. S. Lelis
Procedural generation of initial states of state-space search problems have applications in human and machine learning as well as in the evaluation of planning systems. In this pap…
An LP-Based Approach for Goal Recognition as Planning
Luísa R. de A. Santos, Felipe Meneguzzi, Ramon Fraga Pereira +1
Goal recognition aims to recognize the set of candidate goals that are compatible with the observed behavior of an agent. In this paper, we develop a method based on the operator-c…