q-learning

Solving Hard Bi-objective Knapsack Problems Using Deep Reinforcement Learning

  • Sasan Mahmoudinazlou
  • Hadi Charkhgard
  • Ali Eshragh
    • Categories Approximation Algorithms, Integer Programming Tags , , ,

    We study a class of bi-objective integer programs known as bi-objective knapsack problems (BOKPs). Our research focuses on the development of innovative exact and approximate solution methods for BOKPs by synergizing algorithmic concepts from two distinct domains: multi-objective integer programming and (deep) reinforcement learning. While novel reinforcement learning techniques have been applied successfully to single-objective … Read more

    An Adaptive and Near Parameter-free BRKGA Using Q-Learning Method

  • Antonio Chaves
  • Luiz Henrique Lorena
    • Categories Meta Heuristics Tags , , ,

    The Biased Random-Key Genetic Algorithm (BRKGA) is an efficient metaheuristic to solve combinatorial optimization problems but requires parameter tuning so the intensification and diversification of the algorithm work in a balanced way. There is, however, not only one optimal parameter configuration, and the best configuration may differ according to the stages of the evolutionary process. … Read more

    A Q-Learning Algorithm with Continuous State Space

  • Kengy Barty
  • Pierre Girardeau
  • Jean-Sebastien Roy
  • Cyrille Strugarek
    • Categories Dynamic Programming, Stochastic Programming Tags , ,

    We study in this paper a Markov Decision Problem (MDP) with continuous state space and discrete decision variables. We propose an extension of the Q-learning algorithm introduced to solve this problem by Watkins in 1989 for completely discrete MDPs. Our algorithm relies on stochastic approximation and functional estimation, and uses kernels to locally update the … Read more