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| public:t_720_atai:atai-20:knowledge_representation [2020/10/06 14:53] – [Symbols, Models, Syntax] thorisson | public:t_720_atai:atai-20:knowledge_representation [2024/04/29 13:33] (current) – external edit 127.0.0.1 |
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| | What Now? | Here comes some "glue" for connecting the above concepts, ideas, and claims in a way that unifies it into a coherent story that explains intelligence. | | | What Now? | Here comes some "glue" for connecting the above concepts, ideas, and claims in a way that unifies it into a coherent story that explains intelligence. | |
| | \\ \\ Knowledge | Knowledge is "actionable information" - information structures that can be used to //do stuff//, including \\ (a) predict (deduce), \\ (b) derive potential causes (abduce - like Sherlock Holmes does), \\ ( c) explain, and \\ (d) re-create (like Einstein did with <m>E=mc^2</m>). | | | \\ \\ Knowledge | Knowledge is "actionable information" - information structures that can be used to //do stuff//, including \\ (a) predict (deduce), \\ (b) derive potential causes (abduce - like Sherlock Holmes does), \\ ( c) explain, and \\ (d) re-create (like Einstein did with <m>E=mc^2</m>). | |
| | \\ \\ Knowledge \\ = \\ Models | Sets of models allow a thinking agent to do the above, by \\ (a) finding the relevant models for anything (given a certain situation and active goals), \\ (b) apply them according to the goals to derive predictions, \\ ( c) selecting the right actions based on these predictions such that the goals can be achieved, and \\ (d) monitoring the outcome. \\ (Learning then results from correcting the models that predicted incorrectly.) | | | \\ Knowledge \\ = \\ Models | Sets of models allow a thinking agent to do the above, by \\ (a) finding the relevant models for anything (given a certain situation and active goals), \\ (b) apply them according to the goals to derive predictions, \\ ( c) selecting the right actions based on these predictions such that the goals can be achieved, and \\ (d) monitoring the outcome. \\ (Learning then results from correcting the models that predicted incorrectly.) | |
| | \\ What's Contained \\ in Models? | Models must capture, in some way: \\ - Patterns \\ - Relations \\ - Volitional acts \\ - Causal chains | | | \\ What's Contained \\ in Models? | Models must, on their own or in sets, capture in some way: \\ - Patterns \\ - Relations \\ - Volitional acts \\ - Causal chains | |
| | Where Do The Symbols Come In? | Symbols are mechanisms for rounding up model sets - they are "handles" on the information structures. \\ In humans this "rounding up" happens subconsciously and automatically, most of the time, using similarity mapping (content-driven association). | | | Where Do The Symbols Come In? | Symbols are mechanisms for rounding up model sets - they are "handles" on the information structures. \\ In humans this "rounding up" happens subconsciously and automatically, most of the time, using similarity mapping (content-driven association). | |
| | \\ Syntactic Autonomy | To enable autonomous thought, the use of symbols for managing huge sets of models must follow certain rules. For determining the development of biological agents, these rules - their syntax - must exist in form //a priori// of the developing, learning mind, because it determines what these symbols can and cannot do. In this sense, "syntax" means the "rules of management" of information structures (just like the use of symbols in human communication). | | | \\ Syntactic Autonomy | To enable autonomous thought, the use of symbols for managing huge sets of models must follow certain rules. For determining the development of biological agents, these rules - their syntax - must exist in form //a priori// of the developing, learning mind, because it determines what these symbols can and cannot do. In this sense, "syntax" means the "rules of management" of information structures (just like the use of symbols in human communication). | |
| | What It Is | The establishment of axioms for the world and applying logic to these. | | | What It Is | The establishment of axioms for the world and applying logic to these. | |
| | Depends On | Semantic closure. | | | Depends On | Semantic closure. | |
| | But The World Is Non-Axiomatic ! | Yes. But there is no way to apply logic unless we hypothesize some pseudo-axioms. The only difference between this and mathematics is that in science we must accept that the so-called "laws" of physics may be only conditionally correct (or possibly even completely incorrect, in light of our goal of figuring out the "ultimate" truth about how the universe works). | | | But The World Is Non-Axiomatic ! | \\ Yes. But there is no way to apply logic unless we hypothesize some pseudo-axioms. The only difference between this and mathematics is that in science we must accept that the so-called "laws" of physics may be only conditionally correct (or possibly even completely incorrect, in light of our goal of figuring out the "ultimate" truth about how the universe works). | |
| | Deduction | Results of two statements that logically are necessarily true. \\ //Example: If it's true that all swans are white, and Joe is a swan, then Joe must be white//. | | | Deduction | Results of two statements that logically are necessarily true. \\ //Example: If it's true that all swans are white, and Joe is a swan, then Joe must be white//. | |
| | Abduction | Reasoning from conclusions to causes. \\ //Example: If the light is on, and it was off just a minute ago, someone must have flipped the switch//. | | | Abduction | Reasoning from conclusions to causes. \\ //Example: If the light is on, and it was off just a minute ago, someone must have flipped the switch//. | |
