Abstract
Autonomy is arguably the most important feature of an intelligent agent since it dictates that the agent can make decisions on its own, without any outside help. In simple environments this is not difficult to achieve: a simple search through the possible actions and states will yield the best thing to do in every case, and the associated computation will be tractable. However, the situation changes drastically in complex environments. Agents in these conditions will often need to act under uncertainty; this means that they will not always be sure about what state they are in, nor will they be sure about the outcomes of their actions.
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© 2011 Springer Science+Business Media, LLC
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Simari, G.I., Parsons, S.D. (2011). Introduction. In: Markov Decision Processes and the Belief-Desire-Intention Model. SpringerBriefs in Computer Science. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-1472-8_1
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DOI: https://doi.org/10.1007/978-1-4614-1472-8_1
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