Adaptive control proves to be an important eld of investigation as several control problems change its behaviour in time or there is no analytical model available at all. We present a new approach in this context: A fuzzy controller is adapted according to an evaluation function by a critic that is trained using reinforcement learning. In this paper we address the modeling and adaptation of the...

This paper proposes a control algorithm based on adaptive dynamic programming to solve the infinite-horizon optimal control problem for known deterministic nonlinear systems with saturating actuators and non-quadratic cost functionals. The algorithm is based on an actor/critic framework where a critic neural network is used to learn the optimal cost and an actor neural network is used to learn ...

Critic-proofing is a modified heuristic evaluation technique, specifically designed to provide a fine-grained, prioritized list of heuristic violations. The critic-proofing technique weights the severity of a problem based on the frequency that similar problems are found in similar games. The severity ratings are calculated using data collected from game reviews, and the severity assigned to a ...

This article argues that Russell McCutcheon’s notion of the religion scholar as a critic is crucial for envisioning a distinct relevance to the academic study of religion in multidisciplinary conversations concerning questions of religion and conflict. However, McCutcheon’s critical approach is insufficient for thinking about transforming conflicts and underlying structures of injustice. To act...

Adaptive critic (AC) based controllers are typically discrete and/or yield a uniformly ultimately bounded stability result because of the presence of disturbances and unknown approximation errors. A continuous-time AC controller is developed that yields asymptotic tracking of a class of uncertain nonlinear systems with bounded disturbances. The proposed AC-based controller consists of two neura...

In the present paper a neural network approach called “Adaptive Critic Design” (ACD) was applied to optimal tuning of set point controllers of the three main substrates (sugar, nitrogen source and dissolved oxygen) for PHB production process. For approximation of the critic and the controllers a special kind of recurrent neural networks called Echo state networks (ESN) were used. Their structur...