A Cognitive Agent Model Incorporating Prior and Retrospective Ownership States for Actions
Jan Treur
This paper presents a cognitive agent model generating prior and retrospective ownership states for an action. The model makes use of principles from recent neurological theories. A prior ownership state is affected by prediction of the effects of the action, and may lead to strengthening or suppressing actual execution of the action. Moreover, it is shown how the actual execution and sensing of the effects of the action can lead to a retrospective ownership state, in particular when the sensed consequences co-occur with the predicted consequences. Whereas prior ownership states play an important role in the go/no-go decisions for the execution of prepared actions, retrospective ownership states are the basis for acknowleding authorship of actions, for example, in social context. It is shown how poor action effect prediction capabilities can lead to reduced retrospective ownership states, as is shown in persons suffering from schizophrenia. The presented agent model provides a basis for human-like behaviour of virtual agents in the context of simulation-based training or gaming.