in this paper an approach based on evolutionary algorithms to find pareto optimal pair of state and control for multi-objective optimal control problems (moocp)'s is introduced‎. ‎in this approach‎, ‎first a discretized form of the time-control space is considered and then‎, ‎a piecewise linear control and a piecewise linear trajectory are obtained from the discretized time-control space using ...

We study decentralized stochastic linear bandits, where a network of N agents acts cooperatively to efficiently solve bandit-optimization problem over d-dimensional space. For this problem, we propose DLUCB: fully algorithm that minimizes the cumulative regret entire network. At each round agent chooses its actions following an upper confidence bound (UCB) strategy and share information with th...