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By J. Lu, et al.

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In the field of artificial intelligence, autonomy has been one of the key elements in many research subfields, such as intelligent agents [Jennings and Wooldridge, 1996]. The above is a general definition of autonomy. , entity autonomy, synthetic autonomy, emergent autonomy, and computational system autonomy. 5 (Entity autonomy) Autonomy of an entity refers to its condition or quality of being self-governed, self-determined, and self-directed. It guarantees that the primitive behavior of an entity is free from the explicit control of other entities.

Positions and distance) in the environment. Within the neighborhood of an entity, local interactions can occur and local information can be collected. The ‘define entity representation’ task handles how to characterize an autonomous entity, including its internal states and goals etc. The last task concerning entities, ‘define primitive behavior and behavioral rules’, defines the ways in which an autonomous entity reacts to various information it has collected within its neighborhood and the ways in which it adapts its primitive behavior and behavioral rules.

It describes a set of features that a solution should have rather than a set of steps to obtain such a solution. The object oriented programming (OOP) paradigm is built on the imperative paradigm. It can be viewed as an extension of the imperative paradigm. It encapsulates variables and their operations as classes. As inspired by the object oriented computing paradigm, Shoham proposed an agent oriented programming (AOP) paradigm [Shoham, 1993], where the basic element is an agent characterized by a group of mental parameters, such as beliefs, commitments, and choices.

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