49 citations · 80 across the 4 of their papers we have counts for
4 papers
A study on a Q-Learning algorithm application to a manufacturing assembly problem
Miguel Neves, Miguel Vieira, Pedro Neto
The development of machine learning algorithms has been gathering relevance to address the increasing modelling complexity of manufacturing decision-making problems. Reinforcement…
Deep reinforcement learning applied to an assembly sequence planning problem with user preferences
Miguel Neves, Pedro Neto
Deep reinforcement learning (DRL) has demonstrated its potential in solving complex manufacturing decision-making problems, especially in a context where the system learns over tim…
DistMS: A Non-Portfolio Distributed Solver for Maximum Satisfiability
Miguel Neves, Inês Lynce, Vasco Manquinho
The most successful parallel SAT and MaxSAT solvers follow a portfolio approach, where each thread applies a different algorithm (or the same algorithm configured differently) to s…
Exploiting Resolution-based Representations for MaxSAT Solving
Miguel Neves, Ruben Martins, Mikoláš Janota +2
Most recent MaxSAT algorithms rely on a succession of calls to a SAT solver in order to find an optimal solution. In particular, several algorithms take advantage of the ability of…