Abstract
This study presents a general agent architecture to simulate human-like intelligence. The design philosophy behind the architecture is driven by a combination of Maslow’s theories of needs and Dennett’s intentional notion. Furthermore, to explain motives of intelligent agents, we adopt Alderfer’s theory of needs which revises the ideas of Maslow. Intelligent agents are considered as entities driven by unsatisfied needs, and in order to satisfy those needs they act intentionally. Based on these ideas, we present a three-tiered cognitive agent architecture to mimic many aspects of human intelligence. The reactive layer enables an agent to continuously observe internal and external conditions and act accordingly. The deliberative layer provides the means for learning, planning, confict resolution with other agents, and dispatching tasks to the components in the reactive layer. The causal layer oversees the high-level decision-making and emotion generation processes.
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Aydın, A.O., Orgun, M.A. (2010). The Reactive-Causal Cognitive Agent Architecture. In: Wang, Y., Zhang, D., Kinsner, W. (eds) Advances in Cognitive Informatics and Cognitive Computing. Studies in Computational Intelligence, vol 323. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16083-7_5
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DOI: https://doi.org/10.1007/978-3-642-16083-7_5
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