Two feedback control systems are designed that employ the adaptive critic architecture, which consists of two neural networks, one of which (the critic) tunes the other. The first application is a deadzone compensator, where it is shown that the adaptive critic structure is a natural consequence of the mathematical problem of inversion of an unknown function. In this situation the adaptive crit...

In this paper, we study the effect of adding a value function approximation component (critic) to rollout classification-based policy iteration (RCPI) algorithms. The idea is to use a critic to approximate the return after we truncate the rollout trajectories. This allows us to control the bias and variance of the rollout estimates of the action-value function. Therefore, the introduction of a ...

background: understanding the learning styles of medical students can drive the institutions to adapt instructional materials to enhance students’ learning of knowledge and skills. this study explored the learning styles of undergraduate medical students, comparing gender variations in terms of their significant preferences. materials and methods: a cross-sectional observational study was perfo...

In this article, we propose and analyze a class of actor-critic algorithms. These are two-time-scale algorithms in which the critic uses temporal difference learning with a linearly parameterized approximation architecture, and the actor is updated in an approximate gradient direction, based on information provided by the critic. We show that the features for the critic should ideally span a su...

Intelligent industrial and mobile robots may be considered proven technology in structured environments. Teach programming and supervised learning methods permit solutions to a variety of applications. However, we believe that to extend the operation of these machines to more unstructured environments requires a new learning method. Both unsupervised learning and reinforcement learning are pote...

Thielscher, M., On prediction in Theorist (Research Note), Artificial Intelligence 60 (1993) 283-292. Theorist is a well-known framework and system for nonmonotonic reasoning which provides mechanisms for dealing with both explanations for observations and skeptical prediction. Its current implementation, developed by David Poole and co-workers, uses an algorithm for prediction which holds for ...