Affect and Learning: a computational analysis

In this thesis we have studied the influence of emotion on learning. We have used computational modelling techniques to do so, more specifically, the reinforcement learning paradigm. Emotion is modelled as artificial affect, a measure that denotes the positiveness versus negativeness of a situation to an artificial agent in a reinforcement learning setting. We have done a range of different experiments to study the effect of affect on learning, including the effect on learning if affect is used to control the exploration behaviour of the agent and the effect on learning when affect is communicated by a human (though real-time analysis of that human__s facial expressions) to a simulated robot. We conclude that affect is a useful concept to consider in adaptive agents that learn based on reinforcement learning and that in some cases affect can indeed help the learning process. Further, affective modelling in this way can help understand the psychological processes that underlie influences of affect on cognition. Finally, we have developed a formal notation for a specific type of emotion theory, i.e., cognitive appraisal theory.UBL - phd migration 201

Symbol manipulation by internal simulation of perception and behaviour

symbol manipulation (Newell and Simon, 1972). Symbol manipulation is the processing of symbolic descriptions to produce an output that benefits an objective. Moreover, embodied models of cognitive development concern situated robots that do not rely on symbolic descriptions or on their manipulation (see, e.g., (Schlesinger, 2003)). In this paper, we introduce an embodied model of cognitive development that does rely on symbol manipulation. It has been claimed that internalised interaction with the external environment constitutes symbol manipulation (Phaf and Wolters, 1997). A mechanism to internalise such interaction was suggested in (Hesslow, 2002) as part of the simulation hypothesis. The simulation hypothesis states that conscious thought is based on the ability to simulate perception and behaviou