q2K BHP
Black History Portal
THE BHP WIRE —
HIDDEN TRUTHS
What's New!
THE JOURNEY THROUGH TIME

Explore Black History

Explore the people, places, events, achievements, struggles and stories that shaped our journey.

✊🏾

Civil Rights

Movements, leaders, victories and the continuing fight for equality.

⚙️

Black Inventors

Innovation, patents, science, technology and world-changing contributions.

🏆

Sports

Pioneers, champions, Negro Leagues, records, activism and excellence.

♟️

People

Meet the people whose lives, choices and achievements shaped the journey.

📍

Places

Black towns, communities, institutions and places where history happened.

📜

Events

Moments that changed communities, movements, institutions and the nation.

Enter a person, place, event, or topic.
MY'STORY

The MOVE Fire

This is a personal recollection on the Move fire on May 13, 1985 Philadelphia police fired thousands of rounds at the MOVE house, city officials approved dropping an explosive device on the roof, the resulting fire was allowed to burn, 11 people—including five children—died, and 61 homes were destroyed. Philadelphia City Council later called it a “brutal attack carried out by the City of Philadelphia on its own citizens” and acknowledged that no individual faced criminal consequences for the bombing. One timeline correction worth preserving for the BHP record: the major previous MOVE-police confrontation was August 8, 1978, about seven years before the bombing, not a year or two earlier. Officer James Ramp was killed, other police and firefighters were wounded, nine MOVE members were later convicted, and television cameras recorded police beating Delbert Africa during his arrest. The 1985 MOVE Commission later specifically criticized city planners for failing to adequately use lessons from that 1978 confrontation. And that actually strengthens the point you’re making: 1985 did not happen without precedent or institutional memory. There had already been a deadly confrontation with MOVE, years of conflict, negotiations and police involvement before Osage Avenue.

MORE →
BLACK FACTS
The Truths They Never Taught You...

Ruler of the Mali Empire in the 14th century

Mansa Musa was the ruler of the Mali Empire in West Africa. Details recorded here should be sourced; unknown information is left blank.

MORE →
BHP gathered finds from its connected research sources. Showing the 4 strongest Black History matches.
← BACK TO RESULTS
Wikipedia

Many-valued logic

Many-valued logic (also multi- or multiple-valued logic) is a propositional or predicate calculus in which there are more than two truth values. Traditionally, in Aristotle's logical calculus, there were only two possible values (i.e., true and false) for any proposition. Classical two-valued logic may be extended to n-valued logic for n greater than 2. Those most popular in the literature are three-valued (e.g., Łukasiewicz's and Kleene's, which accept the values true, false, and unknown), four-valued, seven-valued, nine-valued, the finite-valued (finitely-many valued) with more than three values, and the infinite-valued (infinitely-many-valued), such as fuzzy logic and probability logic.

History

[edit]

Aristotle, the "father of (two-valued) logic",[1] accepted the law of excluded middle but made an important distinction about the principle of bivalence. In (De Interpretatione, ch. IX),[2] he argued that statements about future events cannot always be definitively true or false. However, he didn't develop this insight into a systematic multi-valued logic — it remained a specific exception within his classical framework. Logicians followed this Aristotelian logic tradition until the 20th century, consistently using the law of the excluded middle while acknowledging his concerns about future contingents. Systematic alternatives to classical logic only emerged in modern times.

The 20th century introduced the idea of multi-valued logic. The Polish logician and philosopher Jan Łukasiewicz began to create systems of many-valued logic in 1920, using a third value, possible, to deal with Aristotle's paradox of the sea battle. Meanwhile, the American mathematician, Emil L. Post (1921), also introduced the formulation of additional truth degrees with n ≥ 2, where n are the truth values. Later, Jan Łukasiewicz and Alfred Tarski together formulated a logic on n truth values where n ≥ 2. In 1932, Hans Reichenbach formulated a logic of many truth values where n→∞. Kurt Gödel in 1932 showed that intuitionistic logic is not a finitely-many valued logic, and defined a system of Gödel logics intermediate between classical and intuitionistic logic; such logics are known as intermediate logics.

Examples

[edit]

Kleene (strong) K3 and Priest logic P3

[edit]

Kleene's "(strong) logic of indeterminacy" K3 (sometimes ) and Priest's "logic of paradox" add a third undefined or indeterminate truth value I. The truth functions for negation (¬), conjunction (∧), disjunction (∨), implication (→K), and biconditional (↔K) are given by:[3]

¬  
T F
I I
F T
∧ T I F
T T I F
I I I F
F F F F
∨ T I F
T T T T
I T I I
F T I F
→K T I F
T T I F
I T I I
F T T T
↔K T I F
T T I F
I I I I
F F I T

The difference between the two logics lies in how tautologies are defined. In K3 only T is a designated truth value, while in P3 both T and I are. (A logical formula is considered a tautology if it evaluates to a designated truth value). In Kleene's logic I can be interpreted as being underdetermined, being neither true nor false, while in Priest's logic I can be interpreted as being overdetermined, being both true and false. K3 does not have any tautologies, while P3 has the same tautologies as classical two-valued logic.[4]

Bochvar's internal three-valued logic

[edit]

Another logic is Dmitry Bochvar's internal three-valued logic , also called Kleene's weak three-valued logic. Except for negation and biconditional, its truth tables are all different from the above.[5]

∧+ T I F
T T I F
I I I I
F F I F
∨+ T I F
T T I T
I I I I
F T I F
→+ T I F
T T I F
I I I I
F T I T

The intermediate truth value in Bochvar's internal logic can be described as contagious because it propagates in a formula regardless of the value of any other variable.[5]

Belnap logic (B4)

[edit]

Belnap's logic B4 combines K3 and P3. The overdetermined truth value is here denoted as B and the underdetermined truth value as N.

f¬  
T F
B B
N N
F T
f∧ T B N F
T T B N F
B B B F F
N N F N F
F F F F F
f∨ T B N F
T T T T T
B T B T B
N T T N N
F T B N F

Gödel logics Gk and G∞

[edit]

In 1932 Gödel defined[6] a family of many-valued logics, with finitely many truth values , for example has the truth values and has . In a similar manner he defined a logic with infinitely many truth values, , in which the truth values are all the real numbers in the interval . The designated truth value in these logics is 1.

The conjunction and the disjunction are defined respectively as the minimum and maximum of the operands:

Negation and implication are defined as follows:

Gödel logics are completely axiomatisable, that is to say it is possible to define a logical calculus in which all tautologies are provable. The implication above is the unique Heyting implication defined by the fact that the suprema and minima operations form a complete lattice with an infinite distributive law, which defines a unique complete Heyting algebra structure on the lattice.

Łukasiewicz logics Lv and L∞

[edit]

Implication and negation were defined by Jan Łukasiewicz through the following functions:

At first Łukasiewicz used these definitions in 1920 for his three-valued logic , with truth values . In 1922 he developed a logic with infinitely many values , in which the truth values spanned the real numbers in the interval . In both cases the designated truth value was 1.[7]

By adopting truth values defined in the same way as for Gödel logics , it is possible to create a finitely-valued family of logics , the abovementioned and the logic , in which the truth values are given by the rational numbers in the interval . The set of tautologies in and is identical.

Product logic Π

[edit]

In product logic we have truth values in the interval , a conjunction and an implication , defined as follows[8]

Additionally there is a negative designated value that denotes the concept of false. Through this value it is possible to define a negation and an additional conjunction as follows:

and then .

Post logics Pm

[edit]

In 1921 Post defined a family of logics with (as in and ) the truth values . Negation and conjunction and disjunction are defined as follows:

Rose logics

[edit]

In 1951, Alan Rose defined another family of logics for systems whose truth-values form lattices.[9]

Relation to classical logic

[edit]

Logics are usually systems intended to codify rules for preserving some semantic property of propositions across transformations. In classical logic, this property is truth. In a valid argument, the truth of the derived proposition is guaranteed if the premises are jointly true, because the application of valid steps preserves the property. However, that property doesn't have to be that of truth; instead, it can be some other concept.[citation needed]

When there are more than two truth values, rules of inference may be intended to preserve more than just whichever corresponds (in the relevant sense) to truth. For example, in a three-valued logic, sometimes the two greatest truth-values (when they are represented as e.g. positive integers) are designated and the rules of inference preserve these values.

For example, the preserved property could be justification, the foundational concept of intuitionistic logic. Thus, a proposition is not true or false; instead, it is justified or flawed. A key difference between justification and truth, in this case, is that the law of excluded middle doesn't hold: a proposition that is not flawed is not necessarily justified; instead, it's only not proven that it's flawed. The key difference is the determinacy of the preserved property: One may prove that P is justified, that P is flawed, or be unable to prove either. A valid argument preserves justification across transformations, so a proposition derived from justified propositions is still justified. However, there are proofs in classical logic that depend upon the law of excluded middle; since that law is not usable under this scheme, there are propositions that cannot be proven that way.

Suszko's thesis

[edit]

Functional completeness of many-valued logics

[edit]

Functional completeness is a term used to describe a special property of finite logics and algebras. A logic's set of connectives is said to be functionally complete or adequate if and only if its set of connectives can be used to construct a formula corresponding to every possible truth function.[10] An adequate algebra is one in which every finite mapping of variables can be expressed by some composition of its operations.[11]

Classical logic: CL = ({0,1}, ¬, →, ∨, ∧, ↔) is functionally complete, whereas no Łukasiewicz logic or infinitely many-valued logics has this property.[11][12]

We can define a finitely many-valued logic as being Ln ({1, 2, ..., n} ƒ1, ..., ƒm) where n ≥ 2 is a given natural number. Post (1921) proves that assuming a logic is able to produce a function of any mth order model, there is some corresponding combination of connectives in an adequate logic Ln that can produce a model of order m+1.[13]

Applications

[edit]

Known applications of many-valued logic can be roughly classified into two groups.[14] The first group uses many-valued logic to solve binary problems more efficiently. For example, a well-known approach to represent a multiple-output Boolean function is to treat its output part as a single many-valued variable and convert it to a single-output characteristic function (specifically, the indicator function). Other applications of many-valued logic include design of programmable logic arrays (PLAs) with input decoders, optimization of finite-state machines, testing, and verification.

The second group targets the design of electronic circuits that employ more than two discrete levels of signals, such as many-valued memories, arithmetic circuits, and field programmable gate arrays (FPGAs). Many-valued circuits have a number of theoretical advantages over standard binary circuits. For example, the interconnect on and off chip can be reduced if signals in the circuit assume four or more levels rather than only two. In memory design, storing two instead of one bit of information per memory cell doubles the density of the memory in the same die size. Applications using arithmetic circuits often benefit from using alternatives to binary number systems. For example, residue and redundant number systems[15] can reduce or eliminate the ripple-through carries that are involved in normal binary addition or subtraction, resulting in high-speed arithmetic operations. These number systems have a natural implementation using many-valued circuits. However, the practicality of these potential advantages heavily depends on the availability of circuit realizations, which must be compatible or competitive with present-day standard technologies. In addition to aiding in the design of electronic circuits, many-valued logic is used extensively to test circuits for faults and defects. Basically all known automatic test pattern generation (ATG) algorithms used for digital circuit testing require a simulator that can resolve 5-valued logic (0, 1, x, D, D').[16] The additional values—x, D, and D'—represent (1) unknown/uninitialized, (2) a 0 instead of a 1, and (3) a 1 instead of a 0.

A third area of application is in quantum information processing, where the natural computational unit is not necessarily a binary qubit. A qudit is a quantum system with d > 2 discrete levels, and quantum communication protocols using qudits can achieve higher channel capacities and stronger security guarantees than qubit-based protocols. The algebraic structure of qudit operations is naturally described by many-valued logic over the same number of levels, and several research groups have explored synthesis and optimization of qudit quantum circuits using Many-valued logic concepts as a basis. Photonic platforms, in particular, support high-dimensional encoding in degrees of freedom such as frequency, orbital angular momentum, and time bins, making qudit-based quantum communication an active area of experimental development.[17]

Research venues

[edit]

An IEEE International Symposium on Multiple-Valued Logic (ISMVL) has been held annually since 1970. It mostly caters to applications in digital design and verification.[18] There is also a Journal of Multiple-Valued Logic and Soft Computing.[19]

See also

[edit]
Mathematical logic
Philosophical logic
Digital logic

References

[edit]
  1. ^ Hurley, Patrick. A Concise Introduction to Logic, 9th edition. (2006).
  2. ^ Jules Vuillemin, Necessity or Contingency, CSLI Lecture Notes, N°56, Stanford, 1996, pp. 133-167
  3. ^ (Gottwald 2005, p. 19)
  4. ^ Humberstone, Lloyd (2011). The Connectives. Cambridge, Massachusetts: The MIT Press. pp. 201. ISBN 978-0-262-01654-4.
  5. ^ a b (Bergmann 2008, p. 80)
  6. ^ Gödel, Kurt (1932). "Zum intuitionistischen Aussagenkalkül". Anzeiger der Akademie der Wissenschaften in Wien (69): 65f.
  7. ^ Kreiser, Lothar; Gottwald, Siegfried; Stelzner, Werner (1990). Nichtklassische Logik. Eine Einführung. Berlin: Akademie-Verlag. pp. 41ff–45ff. ISBN 978-3-05-000274-3.
  8. ^ Hajek, Petr: Fuzzy Logic. In: Edward N. Zalta: The Stanford Encyclopedia of Philosophy, Spring 2009. ([1])
  9. ^ Rose, Alan (December 1951). "Systems of logic whose truth-values form lattices". Mathematische Annalen. 123: 152–165. doi:10.1007/BF02054946. S2CID 119735870.
  10. ^ Smith, Nicholas (2012). Logic: The Laws of Truth. Princeton University Press. p. 124.
  11. ^ a b Malinowski, Grzegorz (1993). Many-Valued Logics. Clarendon Press. pp. 26–27.
  12. ^ Church, Alonzo (1996). Introduction to Mathematical Logic. Princeton University Press. ISBN 978-0-691-02906-1.
  13. ^ Post, Emil L. (1921). "Introduction to a General Theory of Elementary Propositions". American Journal of Mathematics. 43 (3): 163–185. doi:10.2307/2370324. hdl:2027/uiuo.ark:/13960/t9j450f7q. ISSN 0002-9327. JSTOR 2370324.
  14. ^ Dubrova, Elena (2002). Multiple-Valued Logic Synthesis and Optimization, in Hassoun S. and Sasao T., editors, Logic Synthesis and Verification, Kluwer Academic Publishers, pp. 89-114
  15. ^ Meher, Pramod Kumar; Valls, Javier; Juang, Tso-Bing; Sridharan, K.; Maharatna, Koushik (August 22, 2008). "50 Years of CORDIC: Algorithms, Architectures and Applications" (PDF). IEEE Transactions on Circuits & Systems I: Regular Papers. 56 (9) (published September 9, 2009): 1893–1907. doi:10.1109/TCSI.2009.2025803. S2CID 5465045. Archived (PDF) from the original on October 9, 2022. Retrieved January 3, 2016.
  16. ^ Abramovici, Miron; Breuer, Melvin A.; Friedman, Arthur D. (1994). Digital Systems Testing and Testable Design. New York: Computer Science Press. p. 183. ISBN 978-0-7803-1062-9.
  17. ^ Erhard, Manuel; Krenn, Mario; Zeilinger, Anton (2020). "Advances in high-dimensional quantum entanglement". Nature Reviews Physics. 2 (7): 365–381. arXiv:1911.10006. doi:10.1038/s42254-020-0193-5.
  18. ^ "IEEE International Symposium on Multiple-Valued Logic (ISMVL)". www.informatik.uni-trier.de/~ley. Archived from the original on April 20, 2011. Retrieved April 16, 2011.
  19. ^ "MVLSC home". Archived from the original on March 15, 2014. Retrieved August 12, 2011.

Further reading

[edit]

General

  • Augusto, Luis M. (2017). Many-valued logics: A mathematical and computational introduction. London: College Publications. 340 pages. ISBN 978-1-84890-250-3. Webpage
  • Béziau J.-Y. (1997), What is many-valued logic ? Proceedings of the 27th International Symposium on Multiple-Valued Logic, IEEE Computer Society, Los Alamitos, pp. 117–121.
  • Malinowski, Gregorz, (2001), Many-Valued Logics, in Goble, Lou, ed., The Blackwell Guide to Philosophical Logic. Blackwell.
  • Bergmann, Merrie (2008), An introduction to many-valued and fuzzy logic: semantics, algebras, and derivation systems, Cambridge University Press, ISBN 978-0-521-88128-9
  • Cignoli, R. L. O., D'Ottaviano, I, M. L., Mundici, D., (2000). Algebraic Foundations of Many-valued Reasoning. Kluwer.
  • Malinowski, Grzegorz (1993). Many-valued logics. Clarendon Press. ISBN 978-0-19-853787-8.
  • S. Gottwald, A Treatise on Many-Valued Logics. Studies in Logic and Computation, vol. 9, Research Studies Press: Baldock, Hertfordshire, England, 2001.
  • Gottwald, Siegfried (2005). "Many-Valued Logics" (PDF). Archived from the original on March 3, 2016. {{cite journal}}: Cite journal requires |journal= (help)CS1 maint: bot: original URL status unknown (link)
  • Miller, D. Michael; Thornton, Mitchell A. (2008). Multiple valued logic: concepts and representations. Synthesis lectures on digital circuits and systems. Vol. 12. Morgan & Claypool Publishers. ISBN 978-1-59829-190-2.
  • Hájek P., (1998), Metamathematics of fuzzy logic. Kluwer. (Fuzzy logic understood as many-valued logic sui generis.)

Specific

  • Alexandre Zinoviev, Philosophical Problems of Many-Valued Logic, D. Reidel Publishing Company, 169p., 1963.
  • Prior A. 1957, Time and Modality. Oxford University Press, based on his 1956 John Locke lectures
  • Goguen J.A. 1968/69, The logic of inexact concepts, Synthese, 19, 325–373.
  • Chang C.C. and Keisler H. J. 1966. Continuous Model Theory, Princeton, Princeton University Press.
  • Gerla G. 2001, Fuzzy logic: Mathematical Tools for Approximate Reasoning, Kluwer Academic Publishers, Dordrecht.
  • Novák, V., Perfilieva, I., Močkoř, J., (1999), Mathematical Principles of Fuzzy Logic. Kluwer, Boston.
  • Pavelka J. 1979, On fuzzy logic I: Many-valued rules of inference, Zeitschr. f. math. Logik und Grundlagen d. Math., 25, 45–52.
  • Metcalfe, George; Olivetti, Nicola; Dov M. Gabbay (2008). Proof Theory for Fuzzy Logics. Springer. ISBN 978-1-4020-9408-8. Covers proof theory of many-valued logics as well, in the tradition of Hájek.
  • Hähnle, Reiner (1993). Automated deduction in multiple-valued logics. Clarendon Press. ISBN 978-0-19-853989-6.
  • Azevedo, Francisco (2003). Constraint solving over multi-valued logics: application to digital circuits. IOS Press. ISBN 978-1-58603-304-0.
  • Bolc, Leonard; Borowik, Piotr (2003). Many-valued Logics 2: Automated reasoning and practical applications. Springer. ISBN 978-3-540-64507-8.
  • Stanković, Radomir S.; Astola, Jaakko T.; Moraga, Claudio (2012). Representation of Multiple-Valued Logic Functions. Morgan & Claypool Publishers. doi:10.2200/S00420ED1V01Y201205DCS037. ISBN 978-1-60845-942-1.
  • Abramovici, Miron; Breuer, Melvin A.; Friedman, Arthur D. (1994). Digital Systems Testing and Testable Design. New York: Computer Science Press. ISBN 978-0-7803-1062-9.
[edit]

Source: Wikipedia. Article content is retrieved live through the MediaWiki API.

No preview image
Wikipedia

Many-valued logic

Many-valued logic (also multi- or multiple-valued logic) is a propositional or predicate calculus in which there are more than two truth values. Traditionally, in Aristotle's logical calculus, there were only two possible values (i.e., true and false) for any proposition. Classical two-valued logic may be extended to n-valued logic for n greater than 2. Those most popular in the literature are three-valued (e.g., Łukasiewicz's and Kleene's, which accept the values true, false, and unknown), four-valued, seven-valued, nine-valued, the finite-valued (finitely-many valued) with more than three values, and the infinite-valued (infinitely-many-valued), such as fuzzy logic and probability logic.

MORE →
No preview image
Wikipedia

Three-valued logic

A three-valued logic (also trinary logic, trivalent, ternary, or trilean, sometimes abbreviated 3VL) is any of several many-valued logic systems in which there are three truth values indicating true, false, and some third value. This is contrasted with the more commonly known bivalent logics (such as classical sentential or Boolean logic) which provide only for true and false. Emil Leon Post is credited with first introducing additional logical truth degrees in his 1921 theory of elementary propositions. The conceptual form and basic ideas of three-valued logic were initially published by Jan Łukasiewicz and Clarence Irving Lewis. These were then re-formulated by Grigore Constantin Moisil in an axiomatic algebraic form, and also extended to n-valued logics in 1945.

MORE →
No preview image
Wikipedia

Finite-valued logic

In logic, a finite-valued logic (also finitely many-valued logic) is a propositional calculus in which truth values are discrete. Traditionally, in Aristotle's logic, the bivalent logic, also known as binary logic was the norm, as the law of the excluded middle precluded more than two possible values (i.e., "true" and "false") for any proposition. Modern three-valued logic (ternary logic) allows for an additional possible truth value (i.e. "undecided"). The term finitely many-valued logic is typically used to describe many-valued logic having three or more, but not infinite, truth values. The term finite-valued logic encompasses both finitely many-valued logic and bivalent logic. Fuzzy logics, which allow for degrees of values between "true" and "false", are typically not considered forms of finite-valued logic. However, finite-valued logic can be applied in Boolean-valued modeling, description logics, and defuzzification of fuzzy logic. A finite-valued logic is decidable (sure to determine outcomes of the logic when it is applied to propositions) if and only if it has a computational semantics.

MORE →
No preview image
Wikipedia

Infinite-valued logic

In logic, an infinite-valued logic (or real-valued logic or infinitely-many-valued logic) is a many-valued logic in which truth values comprise a continuous range. Traditionally, in Aristotle's logic, logic other than bivalent logic was abnormal, as the law of the excluded middle precluded more than two possible values (i.e., "true" and "false") for any proposition. Modern three-valued logic (trivalent logic) allows for an additional possible truth value (i.e., "undecided") and is an example of finite-valued logic in which truth values are discrete, rather than continuous. Infinite-valued logic comprises continuous fuzzy logic, though fuzzy logic in some of its forms can further encompass finite-valued logic. For example, finite-valued logic can be applied in Boolean-valued modeling, description logics, and defuzzification of fuzzy logic.

MORE →
TOPIC OF THE DAY

Greenwood / Black Wall Street

Before the 1921 destruction of Tulsa’s Greenwood District, Black residents had created a remarkable center of business and community life. The district included stores, professional offices, entertainment venues and homes owned by Black citizens. Understanding Greenwood means learning what was built—not only what was burned.

MORE →
TRIVIA QUESTION OF THE DAY

Who was the first African-American woman millionaire in the United States?

Madam C.J. Walker