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| public:t-720-atai:atai-20:generality [2020/09/23 13:39] – [Requirements For AGI Systems] thorisson | public:t-720-atai:atai-20:generality [2024/04/29 13:33] (current) – external edit 127.0.0.1 |
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| ====What Do You Mean by "Generality"?==== | ====What Do You Mean by "Generality"?==== |
| | \\ Flexibility: \\ Breadth of task-environments | Enumeration of variety. \\ (By 'variety' we mean the discernibly different states that can be sensed and that make a difference to a controller.) \\ If a system X can operate in more diverse task-environments than system Y, system X is more //flexible// than system Y. | | | Flexibility: \\ Breadth of task-environments | Enumeration of variety. \\ (By 'variety' we mean the discernibly different states that can be sensed and that make a difference to a controller.) \\ If a system X can operate in more diverse task-environments than system Y, system X is more //flexible// than system Y. | |
| | Solution Diversity: \\ Breadth of solutions | If a system X can reliably generate a larger variation of acceptable solutions to problems than system Y, system X is more //powerful// than system Y. | | | Solution Diversity: \\ Breadth of solutions | \\ If a system X can reliably generate a larger variation of acceptable solutions to problems than system Y, system X is more //powerful// than system Y. | |
| | Constraint Diversity: \\ Breadth of constraints on solutions | \\ If a system X can reliably produce acceptable solutions under a higher number of solution constraints than system Y, system X is more //powerful// than system Y. | | | Constraint Diversity: \\ Breadth of constraints on solutions | \\ If a system X can reliably produce acceptable solutions under a higher number of solution constraints than system Y, system X is more //powerful// than system Y. | |
| | Goal Diversity: \\ Breadth of goals | If a system X can meet a wider range of goals than system Y, system X is more //powerful// than system Y. | | | Goal Diversity: \\ Breadth of goals | If a system X can meet a wider range of goals than system Y, system X is more //powerful// than system Y. | |
| | \\ Mission | **R1.** The system must fulfill its mission – the goals and constraints it has been given by its designers – with possibly several different priorities. | This is the very reason we built the system. We should have pretty good ideas as to why. Shared by all AI systems. | | | \\ Mission | **R1.** The system must fulfill its mission – the goals and constraints it has been given by its designers – with possibly several different priorities. | This is the very reason we built the system. We should have pretty good ideas as to why. Shared by all AI systems. | |
| | \\ AILL \\ "After it Leaves the Lab" | **R2.** The system must be designed to be operational in the long-term, without intervention of its designers after it leaves the lab, as dictated by the temporal scope of its mission. | All machine learning methods today are "before it leaves the lab", meaning that the task-environment must be known and clearly delineated beforehand, and the system cannot handle changes to these assumptions. To be more autonomous we must look at the life of these systems "beyond the lab". | | | \\ AILL \\ "After it Leaves the Lab" | **R2.** The system must be designed to be operational in the long-term, without intervention of its designers after it leaves the lab, as dictated by the temporal scope of its mission. | All machine learning methods today are "before it leaves the lab", meaning that the task-environment must be known and clearly delineated beforehand, and the system cannot handle changes to these assumptions. To be more autonomous we must look at the life of these systems "beyond the lab". | |
| | \\ Domain-independence | R3. The system must be domain- and task-independent – but without a strict requirement for determinism: We limit our architecture to handle only missions for which rigorous determinism is not a requirement. | It is easy to implement domain dependence in software systems: Virtually //all// software today is made this way. Domain independence is necessary if we want to build more autonomous systems. | | | \\ Domain-independence | **R3.** The system must be domain- and task-independent – but without a strict requirement for determinism: We limit our architecture to handle only missions for which rigorous determinism is not a requirement. | It is easy to implement domain dependence in software systems: Virtually //all// software today is made this way. Domain independence is necessary if we want to build more autonomous systems. | |
| | \\ Modeling | **R4.** The system must be able to model its environment to adapt to changes thereof. | A good controller not only reacts to changes in its environment, it anticipates them. Anticipation, or prediction, is only possible with a decent model the system whose behavior we are predicting. A good model allows detailed and long-term prediction. | | | \\ Modeling | \\ **R4.** The system must be able to model its environment to adapt to changes thereof. | A good controller not only reacts to changes in its environment, it anticipates them. Anticipation, or prediction, is only possible with a decent model the system whose behavior we are predicting. A good model allows detailed and long-term prediction. | |
| | \\ Anytime | **R5.** As with learning, planning must be performed continuously, incrementally and in real-time. Pursuing goals and predicting must be done concurrently. | A good system learns //all the time// and is planning and revising its plans //all the time//. Anything less makes the system less fit ("dumber"). | | | \\ Anytime | **R5.** As with learning, planning must be performed continuously, incrementally and in real-time. Pursuing goals and predicting must be done concurrently. | A good system learns //all the time// and is planning and revising its plans //all the time//. Anything less makes the system less fit ("dumber"). | |
| | \\ Attention | \\ **R6.** The system must be able to control the focus of its attention. | Any system in a world that is vastly more complex and large than its resources allow to explore at any one time, must select what to apply its thinking, memory, and behavior to. Such "resource management" when applied to thinking is called "attention". | | | \\ Attention | \\ **R6.** The system must be able to control the focus of its attention. | Any system in a world that is vastly more complex and large than its resources allow to explore at any one time, must select what to apply its thinking, memory, and behavior to. Such "resource management" when applied to thinking is called "attention". | |
| | Learning | Acquisition of knowledge that enables more successful completion of tasks and adaptation to environments. | | | Learning | Acquisition of knowledge that enables more successful completion of tasks and adaptation to environments. | |
| | Life-long learning | Incremental acquisition of knowledge throughout a (non-trivially long) lifetime. | | | Life-long learning | Incremental acquisition of knowledge throughout a (non-trivially long) lifetime. | |
| | Cumulative Learning | The ability to integrate new information with that already acquired, in a coherent, efficient and effective manner (seeing what relates to what, resolving conflicts). | | | Cumulative Learning | The ability to unify new information and knowledge that is already acquired, in a coherent, efficient and effective manner (seeing what relates to what, resolving conflicts). | |
| | Transfer learning | The ability to transfer what has been learned in one task to another. | | | Transfer learning | The ability to transfer what has been learned in one task, situation, environment or domain to another task, situation, environment or domain. | |
| | Autonomy | The ability to do tasks without interference / help from others. | | | Autonomy | The ability to do tasks without interference / help from others. | |
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