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| public:t-713-mers:mers-25:concepts_terms [2025/08/19 12:14] – [Reasoning] thorisson | public:t-713-mers:mers-25:concepts_terms [2025/08/19 12:27] (current) – [Correlation, Knowledge, Causation] thorisson |
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| ====Correlation, Knowledge, Causation==== | ====Correlation, Knowledge, Causation==== |
| | Correlation | Some factors/variables co-vary when changes in one variable are related with changes in the other, negative or positive. | | | Correlation | Some factors/variables co-vary when changes in one variable are related with changes in the other, negative or positive. | |
| | Correlation: Powerful source of information | Any variables in the world can be measured for correlation (i.e. to see if they are correlated). Only two variables are needed (independent and dependent) for doing correlation studies. | | | Correlation: Powerful source of information | Any variables in the world can be measured for correlation (i.e. to see if they are correlated). Only two variables are needed (independent and dependent) for doing correlation studies. | |
| | Main operating principle behind correlation | There is no causation without correlation. \\ BUT: It is not guaranteed to be measurable. | | | Main operating principle behind correlation | There is no causation without correlation. \\ BUT: It is not guaranteed to be measurable. | |
| | Correlation: Pitfall | Correlation does not imply causation between the variables measured! \\ BUT: ALL correlation that is NOT a coincidence has a cause. | | | Correlation: Pitfall | Correlation does not imply causation between the variables measured! \\ BUT: ALL correlation that is NOT a coincidence has a cause. | |
| | | Modeling Correlation | A model that makes use of observed correlation between A and B is only good for prediction, not for manipulation; to be useful for manipulation (goal-directed behavior and planning) it must include the causal direction of the relationship between A and B. | |
| | | Causal Relations are Invisible | Causal relations do not jump out at us when we observe something unfamiliar because the cause and effect are "spread out" over time -- cause-effect happens over time, as the cause must happen before the effect. | |
| | | Modeling Cause-Effect | Intelligent agents can model cause and effect with many methods; two of them are invention (coming up with a wild idea for the relationship betweeen A and B, e.g. that spirits make people sick) and discovery (through observation and experimentation with A and B, e.g. that unclean surgical knives can bring disease-carrying material between people). | |
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| ====Reasoning==== | ====Reasoning==== |
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| | What is Reasoning? | A systematic way of considering implications. | | | What is Reasoning? | A systematic way of considering statements and their implications. | |
| | How is it done? | Via processes that observe rules. | | | How is it done? | Via processes that observe rules, called "reasoning processes". | |
| | What are \\ the main reasoning \\ process types? | **Deduction**: All men are mortal. Socrates is a man. Hence, Socrates is mortal \\ **Abduction**: How did this come about? (Sherlock Holmes) \\ **Induction**: What is the general rule? \\ **Analogy**: 'This' is like 'that' (in 'this' way). | | | What are \\ the main reasoning \\ process types? | **Deduction**: All men are mortal. Socrates is a man. Hence, Socrates is mortal \\ **Abduction**: How did this come about? (Sherlock Holmes) \\ **Induction**: What is the general rule? \\ **Analogy**: 'This' is like 'that' (in 'this' way). | |
| | How are they used \\ in science? | In empirical science to unearth the "rules of the universe". \\ In mathematics as axioms. \\ In philosophy as a way to construct arguments. \\ In computer science to write code. | | | How are they used \\ in science? | In empirical science to unearth the "rules of the universe". \\ In mathematics as axioms. \\ In philosophy as a way to construct arguments. \\ In computer science to write code. | |
| | Axiomatic vs. \\ Non-axiomatic | In axiomatic reasoning we know for a fact \\ 1. we have the complete set of rules \\ 2. all the rules are true, and that \\ 3. if we strictly follow the rules we will have absolute truth every time. \\ In non-axiomatic reasoning, none of the above holds. \\ //So how is it then that we can reason?// | | | Axiomatic vs. \\ Non-axiomatic | In axiomatic reasoning we know for a fact \\ 1. we have the complete set of rules \\ 2. all the rules are true, and that \\ 3. if we strictly follow the rules we will have absolute truth every time. \\ In non-axiomatic reasoning, none of the above holds. \\ //So how is it then that we can reason?// | |
| | Empirical Reasoning | For reasoning in the physical world, we must assume that we possibly got things wrong. But //some things are more wrong than others.// To ensure that we use the best knowledge we have for any task X, we must do bookkeeping about //what works and what doesn't in what situations//. | | | Empirical Reasoning | For reasoning in the physical world, we must assume that we possibly got things wrong. But //some things are more wrong than others.// To ensure that we use the best knowledge we have for any task X, we must do bookkeeping about //what works and what doesn't in what situations//. | |
| | | Defeasible Reasoning | Reasoning that is based on assumptions and conclusions that can be refuted is called //defeasible reasoning//. | |
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| | A scientific theory gives us the big picture | A good scientific theory relates together, in a coherent way, some part of the world -- in general the bigger the part, the better the theory. | | | A scientific theory gives us the big picture | A good scientific theory relates together, in a coherent way, some part of the world -- in general the bigger the part, the better the theory. | |
| | Occam's Razor | A good scientific theory cannot be simplified; it is the shortest and most accurate explanation of a phenomenon. Einstein is quoted as saying: "A theory should be as simple as possible, but not simpler". | | | Occam's Razor | A good scientific theory cannot be simplified; it is the shortest and most accurate explanation of a phenomenon. Einstein is quoted as saying: "A theory should be as simple as possible, but not simpler". | |
| | A scientific theory can be **disproven** | A scientific theory or hypothesis is a statement that is //disprovable//. To count as "scientific" a theory //must// be disprovable. For this there must exist some measures and actions that are //possible// (in theory, but better yet, practic) whose results would possibly - should the measurements come out a particular way - disprove the theory. \\ Applying this criterion strictly means that //all scientific theories to date have been disproven - i.e. proven incorrect.// \\ This is not a bug but a //**feature!**:// Exposing the limits of our theories by demonstrating in which contexts they are incorrect allows us to come up with better theories. | | | \\ A scientific theory can be **disproven** | A scientific theory or hypothesis is a statement that is //disprovable//. To count as "scientific" a theory //must// be disprovable. For this there must exist some measures and actions that are //possible// (in theory, but better yet, practic) whose results would possibly - should the measurements come out a particular way - disprove the theory. \\ Applying this criterion strictly means that //all scientific theories to date have been disproven - i.e. proven incorrect.// \\ This is not a bug but a //**feature!**:// Exposing the limits of our theories by demonstrating in which contexts they are incorrect allows us to come up with better theories. | |
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