reinforcement learning

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

    SDP-based bounds for the Quadratic Cycle Cover Problem via cutting plane augmented Lagrangian methods and reinforcement learning

  • Frank de Meijer
  • Renata Sotirov
    • Categories Combinatorial Optimization, Semi-definite Programming Tags , , , , ,

    We study the Quadratic Cycle Cover Problem (QCCP), which aims to find a node-disjoint cycle cover in a directed graph with minimum interaction cost between successive arcs. We derive several semidefinite programming (SDP) relaxations and use facial reduction to make these strictly feasible. We investigate a nontrivial relationship between the transformation matrix used in the … Read more

    Stochastic Primal-Dual Methods and Sample Complexity of Reinforcement Learning

  • Yichen Chen
  • Mengdi Wang
    • Categories Dynamic Programming Tags ,

    We study the online estimation of the optimal policy of a Markov decision process (MDP). We propose a class of Stochastic Primal-Dual (SPD) methods which exploit the inherent minimax duality of Bellman equations. The SPD methods update a few coordinates of the value and policy estimates as a new state transition is observed. These methods … Read more