Autonomy can be defined as the ability of a machine to perform tasks in the absence of human presence. To truly classify a system so that it possesses autonomy, the following three-dimensional approaches can be adopted: Say no to plagiarism. Get a tailor-made essay on "Why Violent Video Games Shouldn't Be Banned"? Get an original essayHuman-machine relationshipcommand-controlThis dimension concerns the involvement of humanity in the operation of systems with autonomy. These systems are divided into the following three types.Semi-Autonomous System: Systems that require human input. Human-supervised systems: Systems that do not require human input to operate but supervision is provided to account for cases of malfunction or failure. Fully autonomous systems: Systems that run on their own without human input. Sophistication in Decision Making This approach deals with the ability to exercise command over one's operations. From this point of view we can divide these systems into three different forms: automatic, automated and autonomous. Automatic refers to the provision of a mechanical response to sensory inputs through predefined protocols. On the other hand, machines that are capable of adapting to changes in their environment as well as a notable level of self-governance can be called autonomous. Types of functions realized autonomously This dimension states that the properties of a system with respect to autonomy depend on each function in particular. Therefore, functions such as navigation could be designed to achieve autonomy without ethical or strategic risks and yet achieving autonomy in targeting systems could be more concerning. Autonomy deals with obtaining data and using it for various actions, the data can be obtained from the environment of the machine. To achieve autonomy, the integration of 3 fundamental capabilities is essential. The core capabilities are: Sense, Decide, Act.Sense - To achieve autonomy, effective perception of the environment through a variety of sensors it may possess is essential. These sensors will obtain data from the environment. It must also use tracking software to properly interpret this data. Target detection, for example, is based on pattern detection. In which the system deciphers patterns from a given dataset, compares them with the predefined patterns stored in its computer's memory and detects the target accordingly. Decide: Data from the tracking software is input for decision making. The course of action can differ greatly depending on the system's perception of its environment. For example, a main battle tank's target acquisition can detect approaching air threats, once the tank commander authorizes retaliation, the tank's autonomous anti-aircraft weapon system can decide its approach in based on factors such as wind speed, target altitude and speed, humidity, and so on.Act - Once the decision-making process is complete, the system exercises its control in the real world by physical or computational means. Decision models can be reactive or deliberative. The reactive model contains prescribed instructions for how the system should behave when faced with certain sets of inputs. For example, in a land mine, the prescribed rule might be that if a weight of between 70 and 100 kg is exerted on it, then it must explode. The deliberative model of decision making understands its environment in mathematical terms and is more complex than the reactive model. Deliberative models possess the capacity to govern.