Abstract
Recent years have witnessed increasing interest in ‘intelligent’ autonomous machines such as robots. However, there is a long way to go before autonomous systems reach the level of capabilities required for even the simplest of tasks involving human-robot interaction - especially if it involves communicative behavior such as speech and language. The field of Artificial Intelligence (AI) has made great strides in these areas, and has graduated from high-level rule-based paradigms to embodied architectures whose operations are grounded in real physical environments. What is still missing, however, is an overarching theory of intelligent communicative behavior that informs system-level design decisions. This chapter introduces a framework that extends the principles of Perceptual Control Theory (PCT) toward a remarkably symmetric architecture for a needs-driven communicative agent. It is concluded that, if behavior is the control of perception (the central tenet of PCT), then perception (for communicative agents) is the simulation of behavior.
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