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| public:t-720-atai:atai-19:lecture_notes:autonomy [2019/10/14 20:39] – [Autonomy & Closure] thorisson | public:t-720-atai:atai-19:lecture_notes:autonomy [2024/04/29 13:33] (current) – external edit 127.0.0.1 |
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| | Self-Inspection | Virtually no systems exist as of yet that has been demonstrated to be able to inspect (measure, quantify, compare, track, make use of) their own development for use in its continued growth - whether learning, goal-generation, selection of variables, resource usage, or other self-X. | | | Self-Inspection | Virtually no systems exist as of yet that has been demonstrated to be able to inspect (measure, quantify, compare, track, make use of) their own development for use in its continued growth - whether learning, goal-generation, selection of variables, resource usage, or other self-X. | |
| | Self-Growth | No System as of yet has been demonstrated to be able to autonomously manage its own **self-growth**. Self-Growth is necessary for autonomous learning in task-environments with complexities far higher than the controller operating in it. It is even more important where certain bootstrapping thresholds are necessary before safe transition into more powerful/different learning schemes. \\ For instance, if only a few bits of knowledge can be programmed into a controller's seed ("DNA"), because we want it to have maximal flexibility in what it can learn, then we want to put something there that is essential to protect the controller while it develops more sophisticated learning. An example is that nature programmed human babies with an innate fear of heights. | | | Self-Growth | No System as of yet has been demonstrated to be able to autonomously manage its own **self-growth**. Self-Growth is necessary for autonomous learning in task-environments with complexities far higher than the controller operating in it. It is even more important where certain bootstrapping thresholds are necessary before safe transition into more powerful/different learning schemes. \\ For instance, if only a few bits of knowledge can be programmed into a controller's seed ("DNA"), because we want it to have maximal flexibility in what it can learn, then we want to put something there that is essential to protect the controller while it develops more sophisticated learning. An example is that nature programmed human babies with an innate fear of heights. | |
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| | ==== Autonomy & Closure ==== |
| | | Autonomy | The ability to do tasks without interference / help from others in a particular task-environment in a particular world. | |
| | | Cognitive Autonomy | Refers to the mental (control-) independence of agents - the more independent they are (of their designers, of outside aid, etc.) the more autonomous they are. Systems without it could hardly be considered to have general intelligence. | |
| | | Structural Autonomy | Refers to the process through which cognitive autonomy is achieved: Motivations, goals and behaviors as dynamically and continuously (re)constructed by the machine as a result of changes in its internal structure. | |
| | | Operational closure | The system's own operations is all that is required to maintain (and improve) the system itself. | |
| | | \\ Semantic closure | The system's own operations and experience produces/defines the meaning of its constituents. //Meaning// can thus be seen as being defined/given by the operation of the system as a whole: the actions it has taken, is taking, could be taking, and has thought about (simulated) taking, both cognitive actions and external actions in its physical domain. For instance, the **meaning** of the act of punching your best friend are the implications of that act - actual and potential - that this action has/may have, and its impact on your own and others' cognition. | |
| | | Self-Programming in Autonomy | The global process that animates computational structurally autonomous systems, i.e. the implementation of both the operational and semantic closures. | |
| | | System evolution | A controlled and planned reflective process; a global and never-terminating process of architectural synthesis. | |
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| ==== Autonomy & Closure ==== | |
| | Autonomy | The ability to do tasks without interference / help from others in a particular task-environment in a particular world. | | |
| | Cognitive Autonomy | Refers to the mental (control-) independence of agents - the more independent they are (of their designers, of outside aid, etc.) the more autonomous they are. Systems without it could hardly be considered to have general intelligence. | | |
| | Structural Autonomy | Refers to the process through which cognitive autonomy is achieved: Motivations, goals and behaviors as dynamically and continuously (re)constructed by the machine as a result of changes in its internal structure. | | |
| | Operational closure | The system's own operations is all that is required to maintain (and improve) the system itself. | | |
| | \\ Semantic closure | The system's own operations and experience produces/defines the meaning of its constituents. //Meaning// can thus be seen as being defined/given by the operation of the system as a whole: the actions it has taken, is taking, could be taking, and has thought about (simulated) taking, both cognitive actions and external actions in its physical domain. For instance, the **meaning** of the act of punching your best friend are the implications of that act - actual and potential - that this action has/may have, and its impact on your own and others' cognition. | | |
| | Self-Programming in Autonomy | The global process that animates computational structurally autonomous systems, i.e. the implementation of both the operational and semantic closures. | | |
| | System evolution | A controlled and planned reflective process; a global and never-terminating process of architectural synthesis. | | |
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