These experiments showed a link between being cognitively engaged and the ability to participate successfully in a standard experiment. The experiments also suggested that an important factor in the individuals ability to perform these tasks is their arousal level. This existing work could be extended in various ways. Antonio R. Damasio. Modelling Affect in AI Standard AI problem solving algorithms run to completion to find the best solution to a problem given the model of the problem used and the training data available.
Human problem solving is rather different.
In general humans do not systematically explore all possible solutions to a problem, but rather focus quickly on likely areas for a good solution and are able to reach rapid approximate solutions. In operations this markers disuade us from certain possible solution areas, often subconsciously, due to their associations with previous negative experiences. Sloman argues that this model is wrong and explores the ideas of a metamagement system independent of emotions. The aim of this project would be explore the modelling of meta management based on observed human problems solving into AI problem solving algorithms. These could be based on direct models of emotion, in effect modelling somatic markers, or a more abstract notion of metamanagement.