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Understanding the nature of consciousness has been an outstanding scientific puzzle at the crossroads of neuroscience and artificial intelligence. While brains have long since known to be the bearers of consciousness and machines, that of computation, the history of cybernetics has been full of attempts trying to synthesize consciousness in computational architectures. In recent years, ideas from control theory have proven to be extremely useful for addressing systems-level questions in neuroscience and designing cognitive architectures. Extending these ideas to the study of consciousness, we discuss the core functions of consciousness and control architectural specifications of agents capable of operationalizing these functionalities. We suggest that evolutionary pressures on social dynamics of interacting agents leads to the emergence of consciousness, which is a process for predicting intentional states of other agents (and self) in order to generate social cooperative and competitive behaviors necessary to optimize an agent's survival drives in a world with limited resources.
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