Cognitive architectures for affect and motivation

General frameworks of mind map across tasks and domains. By what means can a general architecture know when it has adapted to a specific task, a particular environment or a specific state of a previously known environment? Our current work on this theme presents an affect- and affordance-based core for mind. This draws on evidence from neuroscience, philosophy and psychology. However, we differentiate between the mechanisms and processes thought to be allied to cognition and intelligent behaviour in biological architectures and the foundational requirements necessary for similarly intelligent behaviour or cognitive-like processes to exist in synthetic architectures. Work on emotion is a morass of definitions and competing theories. We suggest that we should not further this confused framework with unnecessary (and often unneeded) models of emotion for artificial systems. Rather, we should look to foundational requirements for intelligent systems and ask do we require emotions in machines or an alternative equivalent, for example affect, of use in control and self-regulation? This paper addresses this issue with experimentation in a number of simulated and robotic test-beds