Μετάφραση και ανάλυση λέξεων από την τεχνητή νοημοσύνη ChatGPT
Σε αυτήν τη σελίδα μπορείτε να λάβετε μια λεπτομερή ανάλυση μιας λέξης ή μιας φράσης, η οποία δημιουργήθηκε χρησιμοποιώντας το ChatGPT, την καλύτερη τεχνολογία τεχνητής νοημοσύνης μέχρι σήμερα:
- πώς χρησιμοποιείται η λέξη
- συχνότητα χρήσης
- χρησιμοποιείται πιο συχνά στον προφορικό ή γραπτό λόγο
- επιλογές μετάφρασης λέξεων
- παραδείγματα χρήσης (πολλές φράσεις με μετάφραση)
- ετυμολογία
reasoning$67189$ - translation to ελληνικό
![[[Argument]] terminology used in [[logic]]](https://commons.wikimedia.org/wiki/Special:FilePath/Argument terminology used in logic (en).svg?width=200 "[[Argument]] terminology used in [[logic]]")
.JPG?width=200 "Sculpture of Socrates")
![open source statistical package]]](https://commons.wikimedia.org/wiki/Special:FilePath/Gretl screenshot.png?width=200 "open source statistical package]]")
![[[Scatter plot]]s and [[line chart]]s are used in [[descriptive statistics]] to show the observed relationships between different variables, here using the [[Iris flower data set]].](https://commons.wikimedia.org/wiki/Special:FilePath/Iris Pairs Plot.svg?width=200 "[[Scatter plot]]s and [[line chart]]s are used in [[descriptive statistics]] to show the observed relationships between different variables, here using the [[Iris flower data set]].")
![Bernoulli's ''[[Ars Conjectandi]]'' was the first work that dealt with [[probability theory]] as currently understood.](https://commons.wikimedia.org/wiki/Special:FilePath/Jakob Bernoulli.jpg?width=200 "Bernoulli's ''[[Ars Conjectandi]]'' was the first work that dealt with [[probability theory]] as currently understood.")
![[[Karl Pearson]], a founder of mathematical statistics.](https://commons.wikimedia.org/wiki/Special:FilePath/Karl Pearson, 1910.jpg?width=200 "[[Karl Pearson]], a founder of mathematical statistics.")
.svg?width=200 "A least squares fit: in red the points to be fitted, in blue the fitted line.")
![[[Confidence intervals]]: the red line is true value for the mean in this example, the blue lines are random confidence intervals for 100 realizations.](https://commons.wikimedia.org/wiki/Special:FilePath/NYW-confidence-interval.svg?width=200 "[[Confidence intervals]]: the red line is true value for the mean in this example, the blue lines are random confidence intervals for 100 realizations.")
![critical region]] is the set of values to the right of the observed data point (observed value of the test statistic) and the [[p-value]] is represented by the green area.](https://commons.wikimedia.org/wiki/Special:FilePath/P-value in statistical significance testing.svg?width=200 "critical region]] is the set of values to the right of the observed data point (observed value of the test statistic) and the [[p-value]] is represented by the green area.")
![The [[confounding variable]] problem: ''X'' and ''Y'' may be correlated, not because there is causal relationship between them, but because both depend on a third variable ''Z''. ''Z'' is called a confounding factor.](https://commons.wikimedia.org/wiki/Special:FilePath/Simple Confounding Case.svg?width=200 "The [[confounding variable]] problem: ''X'' and ''Y'' may be correlated, not because there is causal relationship between them, but because both depend on a third variable ''Z''. ''Z'' is called a confounding factor.")
Ορισμός
Βικιπαίδεια
In computer science, in particular in knowledge representation and reasoning and metalogic, the area of automated reasoning is dedicated to understanding different aspects of reasoning. The study of automated reasoning helps produce computer programs that allow computers to reason completely, or nearly completely, automatically. Although automated reasoning is considered a sub-field of artificial intelligence, it also has connections with theoretical computer science and philosophy.
The most developed subareas of automated reasoning are automated theorem proving (and the less automated but more pragmatic subfield of interactive theorem proving) and automated proof checking (viewed as guaranteed correct reasoning under fixed assumptions). Extensive work has also been done in reasoning by analogy using induction and abduction.
Other important topics include reasoning under uncertainty and non-monotonic reasoning. An important part of the uncertainty field is that of argumentation, where further constraints of minimality and consistency are applied on top of the more standard automated deduction. John Pollock's OSCAR system is an example of an automated argumentation system that is more specific than being just an automated theorem prover.
Tools and techniques of automated reasoning include the classical logics and calculi, fuzzy logic, Bayesian inference, reasoning with maximal entropy and many less formal ad hoc techniques.
