User:Phlsph7/Semantics - In various disciplines
In various disciplines
[edit]Logic
[edit]Logicians study correct reasoning and often develop formal languages to express arguments and assess their correctness.[1] One part of this process is to provide a semantics for a formal language to precisely define what its terms mean. A semantics of a formal language is a set of rules, usually expressed as a mathematical function, that assigns meanings to formal language expressions.[2] For example, the language of first-order logic uses lowercase letters for individual constants and uppercase letters for predicates. To express the sentence "Bertie is a dog", the formula can be used where is an individual constant for Bertie and is a predicate for dog. Classical model-theoretic semantics assigns meaning to these terms by defining an interpretation function that maps individual constants to specific objects and predicates to sets of objects or tuples. The function maps to Bertie and to the set of all dogs. This way, it is possible to calculate the truth value of the sentence: it is true if Bertie is a member of the set of dogs and false otherwise.[3]
Formal logic aims to determine whether arguments are deductively valid, that is, whether the premises entail the conclusion.[4] Entailment can be defined in terms of syntax or in terms of semantics. Syntactic entailment, expressed with the symbol , relies on rules of inference, which can be understood as procedures to transform premises and arrive at a conclusion. These procedures only take the logical form of the premises on the level of syntax into account and ignore what meaning they express. Semantic entailment, expressed with the symbol , looks at the meaning of the premises, in particular, at their truth value. A conclusion follows semantically from a set of premises if the truth of the premises ensures the truth of the conclusion, that is, if any semantic interpretation function that assigns the premises the value true also assigns the conclusion the value true.[5]
Computer science
[edit]In computer science, the semantics of a program is how it operates when a computer runs it. Semantics contrasts with syntax, which is the form used to express instructions. Different forms of syntax are usually available to describe the same behavior. In Javascript, this is the case for the commands i += 1
and i = i + 1
, which are syntactically different expressions to increase the value of the variable i by one. This difference is also reflected in different programming languages since they rely on different syntax but can usually be employed to create programs with the same behavior on the semantic level.[6]
Static semantics focuses on semantic aspects that affect the compilation of a program. In particular, it is concerned with detecting errors of syntactically correct programs, such as type errors, which arise when an operation receives an incompatible data type. This is the case, for instance, if a function performing a numerical calculation is given a string instead of a number as an argument.[7] Dynamic semantics focuses on the run time behavior of programs, that is, what happens during the execution of instructions.[8] The main approaches to dynamic semantics are denotational, axiomatic, and operational semantics. Denotational semantics relies on mathematical formalisms to describe the effects of each element of the code. Axiomatic semantics uses deductive logic to analyze which conditions must be in place before and after the execution of a program. Operational semantics interprets the execution of a program as a series of steps, each involving the transition from one state to another state.[9]
Psychology
[edit]Psychological semantics examines psychological aspects of meaning. It is concerned with how meaning is represented on a cognitive level and what mental processes are involved in understanding and producing language. It further investigates how meaning interacts with other mental processes, such as the relation between language and perceptual experience.[10][a] Other issues concern how people learn new words and relate them to familiar things and concepts, how they infer the meaning of compound expressions they have never heard before, how they resolve ambiguous expressions, and how semantic illusions lead them to misinterpret sentences.[12]
One key topic is semantic memory, which is a form of general knowledge of meaning that includes the knowledge of language, concepts, and facts. It contrasts with episodic memory, which records events that a person experienced in their life. The comprehension of language relies on semantic memory and the information it carries about word meanings.[13] According to a common view, word meanings are stored and processed in relation to their semantic features. The feature comparison model states that sentences like "a robin is a bird" are assessed on a psychological level by comparing the semantic features of the word robin with the semantic features of the word bird. The assessment process is fast if their semantic features are similar, which is the case if the example is a prototype of the general category. For atypical examples, as in the sentence "a penguin is a bird", there is less overlap in the semantic features and the psychological process is significantly slower.[14]
References
[edit]- Magnus, P. D.; Button, Tim; Thomas-Bolduc, Aaron; Zach, Richard; Loftis, J. Robert; Trueman, Robert (2021). forall x: Calgary: An Introduction to Formal Logic (PDF). Calgary: University of Calgery. ISBN 979-8527349504. Archived (PDF) from the original on 16 February 2023. Retrieved 27 March 2023.
- Mosses, Peter D. (30 June 2003). "The Varieties of Programming Language Semantics (And Their Uses)". In Bjørner, Dines; Broy, Manfred; Zamulin, Alexandre (eds.). Perspectives of System Informatics: 4th International Andrei Ershov Memorial Conference, PSI 2001, Akademgorodok, Novosibirsk, Russia, July 2-6, 2001, Revised Papers. Springer. ISBN 978-3-540-45575-2.
- Fritzson, Peter (31 August 2010). Principles of Object-Oriented Modeling and Simulation with Modelica 2.1. John Wiley & Sons. ISBN 978-0-470-93761-7.
- O’Regan, Gerard (10 January 2020). Mathematics in Computing: An Accessible Guide to Historical, Foundational and Application Contexts. Springer Nature. ISBN 978-3-030-34209-8.
- Dale, Nell B.; Weems, Chip; Headington, Mark R. (2003). Programming and Problem Solving with Java. Jones & Bartlett Learning. ISBN 978-0-7637-0490-2.
- Gregory, Paul A. (30 April 2017). Formal Logic. Broadview Press. ISBN 978-1-77048-594-5.
- Jaakko, Hintikka; Sandu, Gabriel (29 November 2006). "What is Logic?". Philosophy of Logic. Elsevier. ISBN 978-0-08-046663-7.
- Jansana, Ramon (2022). "Algebraic Propositional Logic". The Stanford Encyclopedia of Philosophy. Metaphysics Research Lab, Stanford University. Retrieved 19 February 2024.
- Shapiro, Stewart; Kouri Kissel, Teresa (2024). "Classical Logic". The Stanford Encyclopedia of Philosophy. Metaphysics Research Lab, Stanford University. Retrieved 19 February 2024.
- Johnstone, P. T. (8 October 1987). Notes on Logic and Set Theory. Cambridge University Press. ISBN 978-0-521-33692-5.
- Forster, Thomas (21 July 2003). Logic, Induction and Sets. Cambridge University Press. ISBN 978-0-521-53361-4.
- Grimm, Stephan (19 September 2009). "Knowledge Representation and Ontologies". In Gaber, Mohamed Medhat (ed.). Scientific Data Mining and Knowledge Discovery: Principles and Foundations. Springer Science & Business Media. ISBN 978-3-642-02788-8.
- Cohen, Jonathan (25 June 2009). The Red and the Real: An Essay on Color Ontology. Oxford University Press. ISBN 978-0-19-160960-2.
- Halpern, Diane F.; Voĭskunskiĭ, Aleksandr (1997). States of Mind: American and Post-Soviet Perspectives on Contemporary Issues in Psychology. Oxford University Press. ISBN 978-0-19-510351-9.
- Hampton, James A. (30 July 2015). "7. Categories, Prototypes, and Exemplars". In Riemer, Nick (ed.). The Routledge Handbook of Semantics. Routledge. ISBN 978-1-317-41245-8.
- Tulving, Endel (4 September 2001). "Episodic vs. Semantic Memory". In Wilson, Robert A.; Keil, Frank C. (eds.). The MIT Encyclopedia of the Cognitive Sciences (MITECS). MIT Press. ISBN 978-0-262-73144-7.
- Shi, Zhongzhi (17 February 2017). Mind Computation. World Scientific. ISBN 978-981-314-582-5.
- Smith, Edward E.; Rips, Lance J.; Shoben, Edward J. (19 February 1975). "Semantic Memory and Psychological Semantics". In Bower, Gordon H. (ed.). The Psychology of Learning and Motivation. Academic Press. ISBN 978-0-08-086359-7.
- Fernández, Maribel (8 July 2014). Programming Languages and Operational Semantics: A Concise Overview. Springer. ISBN 978-1-4471-6368-8.
- Sanford, A. J. (2009). "Psychology, Semantics in". In Allan, Keith (ed.). Concise Encyclopedia of Semantics. Elsevier. ISBN 978-0-08-095969-6.
- ^
- Riemer 2010, pp. 173–174
- Jaakko & Sandu 2006, pp. 13–14
- Shapiro & Kouri Kissel 2024, Lead Section, § 2. Language
- ^
- Shapiro & Kouri Kissel 2024, Lead Section, § 4. Semantics
- Jansana 2022, § 5. Algebraic semantics
- Jaakko & Sandu 2006, pp. 17–18
- ^
- Grimm 2009, pp. 116–117
- Shapiro & Kouri Kissel 2024, Lead Section, § 4. Semantics
- Magnus et al. 2021, pp. 193–195
- ^
- Riemer 2010, pp. 173–174
- Jaakko & Sandu 2006, pp. 13–14
- Shapiro & Kouri Kissel 2024, Lead Section
- Gregory 2017, p. 82
- ^
- Forster 2003, pp. 74–75
- Johnstone 1987, p. 23
- Shapiro & Kouri Kissel 2024, Lead Section, § 4. Semantics
- Jaakko & Sandu 2006, pp. 17–20
- ^
- ^
- Fernández 2014, pp. 14–15
- Fritzson 2010, p. 703
- Mosses 2003, p. 167
- ^
- Fernández 2014, pp. 15–16
- Fritzson 2010, p. 703
- Mosses 2003, p. 167
- ^
- Fernández 2014, p. 16
- O’Regan 2020, pp. 193–194
- ^
- Smith, Rips & Shoben 1975, pp. 1–3
- Sanford 2009, p. 792–793, 796
- ^
- Halpern & Voĭskunskiĭ 1997, p. 21
- Cohen 2009, p. 59
- ^ Sanford 2009, p. 793–797
- ^
- Smith, Rips & Shoben 1975, pp. 3–4
- Hampton 2015, p. 125
- Tulving 2001, p. 278
- ^
- Sanford 2009, p. 792
- Smith, Rips & Shoben 1975, pp. 3–4, 42
- Hampton 2015, p. 125–128
- Shi 2017, pp. 85–86
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