The most common explanation for joint-action effects has been the action co-representation account in which observation of another's action is represented within one's own action system. However, recent evidence has shown that the most prominent of these joint-action effects (i.e., the Social Simon effect), can occur when no co-actor is present. In the current work we examined whether another j...

Q-Iearning is a reinforcement learning alg()rithm that learns expected utilities for stateaction transitions through successive interactions with the environment The algorithm '5 simplicity as well as its convergence properties have made it a popular algorithm for study However; its non-parametric representation of utilities limits its effectiveness in environments with large amounts of percept...

abstract background: patient education is among the lowest met need of patients in iran; therefore, expansion of that role can result in greater professional accountability. this study aimed to explain the practical science of the process, structure, and outcomes of a nurse‑led action research project to expand the nurses’ role in patient education in iran. materials and methods: this study was...

This paper reviews the considerable statistical research that has been performed in an attempt to characterize the joint action of two or more chemicals from both a statistical modelling and an underlying biological mechanism point of view. Particular attention is paid to the traditional descriptions of joint toxic action, i.e. independent joint action, similar joint action, and synergistic act...