The retrofitting of heritage buildings represents a significant opportunity to reduce the carbon footprint of our built environment. Within the retrofit process, the desi [...]

Abstrakt: One of the main requests in engineering practice is to have an effective design procedure of a reinforced concrete continuous beam. This task is a multidimensio [...]

In order to simulate a launch, all space instruments undergo a vibration tests. Due to the fixing points in vibrating machines being different, adapters are used for each [...]

Abstrakt:

Asynchronous electric motor control task can be successfully solved using reinforcement learning based method called Q-learning. The main problem to solve is the converge [...]

This paper presents discrete optimization of reinforced concrete structures based on an efficient combination of deterministic and stochastic optimization strategies. The [...]

The dynamic properties of rotor supported on passive magnetic bearings is investigated by means of numerical solution and by measurement on the prototype of experimental [...]

Modifications of reinforcement learning algorithm, so called continuous action reinforcement learning automaton (CARLA), are presented in this contribution. Automaton lea [...]

Q-learning is the most popular and effective version of Reinforcement Learning algorithms. In this paper we discuss the possibility of control of a nonstationary system b [...]

Presented paper is concerned with the numerical modeling of quasibrittle materials such as concrete. Brancherie and Ibrahimbegovic are authors of a simple model capable o [...]

Locally Weighted Learning (LWR) is a class of approximations, based on a local model. In this paper we demonstrate using LWR together with Q-learning for control tasks. Q [...]

Abstrakt: Possible discretization technique oj the continuous state space oj Jour-Iegged robot using simultaneous compositions oj behaviors is described in this contribut [...]

Algorithm of locally weighted regression is presented in this contribution. Local approximator repeatedly uses the locally linear model based on least square method. Simu [...]

Control design of rotating shaft levitated by active magnetic bearing is described in this contribution. Genetic algorithm is used to design controller parameters. Depend [...]

Q-learning method proved to be usable in active magnetic bearing (AMB) control task, however the learning speed remains the main problem. Two-phase variant of the Q-learn [...]

Abstrakt: A great intention is lately focused on Reinforcement Learning (RL) methods. The article is focused on improving model free RL method known as Q-Iearning algorit [...]