<p>This dissertation discusses the view that embodied cognition is essentially internal simulation (or emulation) of perception and action, and that the same (neural) mechanisms are underlying both real and simulated perception and action. More specifically, it surveys evidence supporting the simulation view from different areas of cognitive science (neuroscience, perception, psychology, social cognition, theory of mind). This is integrated with related research in situated robotics and directions for future work on internal simulation of perception and action in robots are outlined. In sum, the ideas discussed here provide an alternative view of representation, which is opposed to the traditional correspondence notions of representation that presuppose objectivism and functionalism. Moreover, this view is suggested as a viable route for situated robotics, which due to its rejection of traditional notions of representation so far has mostly dealt with more or less reactive behavior, to scale up to a cognitive robotics, and thus to further contribute to cognitive science and the understanding of higher-level cognition</p>

<p>In the recent years a growing interest in Cognitive Science has been directed to the cognitive role of the agent's ability to predict the consequences of their actions, without actual engagement with their environment. The creation of an experimental model for Hesslow's simulation hypothesis, based on the use of a simulated adaptive agent and the methods of evolutionary robotics within the general perspective of radical connectionism, is reported in this dissertation. A hierarchical architecture consisting of a mixture of (recurrent) experts is investigated in order to test its ability to produce an 'inner world', functional stand-in for the agent's interactions with its environment. Such a mock world is expected to be rich enough to sustain 'blind navigation', which means navigation based solely on the agent's own internal predictions. The results exhibit the system's vivid internal dynamics, its critical sensitivity to a high number of parameters and, finally, a discrepancy with the declared goal of blind navigation. However, given the dynamical complexity of the system, further analysis and testing appear necessary.</p>

This dissertation discusses the view that embodied cognition is essentially internal simulation (or emulation) of perception and action, and that the same (neural) mechanisms are underlying both real and simulated perception and action. More specifically, it surveys evidence supporting the simulation view from different areas of cognitive science (neuroscience, perception, psychology, social cognition, theory of mind). This is integrated with related research in situated robotics and directions for future work on internal simulation of perception and action in robots are outlined. In sum, the ideas discussed here provide an alternative view of representation, which is opposed to the traditional correspondence notions of representation that presuppose objectivism and functionalism. Moreover, this view is suggested as a viable route for situated robotics, which due to its rejection of traditional notions of representation so far has mostly dealt with more or less reactive behavior, to scale up to a cognitive robotics, and thus to further contribute to cognitive science and the understanding of higher-level cognition

In the recent years a growing interest in Cognitive Science has been directed to the cognitive role of the agent's ability to predict the consequences of their actions, without actual engagement with their environment. The creation of an experimental model for Hesslow's simulation hypothesis, based on the use of a simulated adaptive agent and the methods of evolutionary robotics within the general perspective of radical connectionism, is reported in this dissertation. A hierarchical architecture consisting of a mixture of (recurrent) experts is investigated in order to test its ability to produce an 'inner world', functional stand-in for the agent's interactions with its environment. Such a mock world is expected to be rich enough to sustain 'blind navigation', which means navigation based solely on the agent's own internal predictions. The results exhibit the system's vivid internal dynamics, its critical sensitivity to a high number of parameters and, finally, a discrepancy with the declared goal of blind navigation. However, given the dynamical complexity of the system, further analysis and testing appear necessary.