PolicyAdaptationForVehicleRouting

equivalently this means that if two policies are taken in the space, then their stochas- tic mixture also belongs to the space—, then any (approximate) local optimum of the

Given the simulations are expensive, the problem is here considered determinis- tic (no noise in the initial state nor in the chosen action)... a) Setup of the acrobot problem.

We developed an parameter-updating algorithm for on-line signature verification considering deterioration of verification performance caused by intersession vari- ability in

Table 8 gives the time of the parallel algorithm for various numbers of slaves, with random slaves and various fixed playout times.. random evaluation when the fixed playout time

At the language level, we describe an executable specification language that is expressive enough to control complex systems, while retaining the possibility to perform

In Section 3, the Nested Monte-Carlo Search is presented, in Section 4 we present the Nested Rollout Policy Adaptation algorithm, and in Section 5 the improvement done on the

Playout Policy Adaptation with move Features (PPAF) is a state of the art MCTS algorithm that learns a playout policy online.. We propose a simple modification to PPAF consisting

For all the following work, we shall call SSGA(µ, τ) the algorithm where each one of the µ parents produces a child (with an operator among the predefined