An Algebraic Theory of Information: An Introduction and Survey
Abstract
:1. Introduction: Modeling Information
2. Labeled Algebras
2.1. Modeling Questions
- (1)
- Reflexivity: x ≤ x for all x ∈ Q.
- (2)
- Antisymmetry: x ≤ y and y ≤ x imply x = y.
- (3)
- Transitivity: x ≤ y and y ≤ z imply x ≤ z.
2.2. Labeled Information
- (1)
- Labeling: d: Ψ → Q; ψ ↦ d(ψ).
- (2)
- Combination: ·: Ψ × Ψ → Ψ; ψ, ϕ ↦ ψ · ϕ.
- (3)
- Projection: π : Ψ × Q → Ψ; ψ, x ↦ πx(ψ), defined for x ≤ d(ψ).
- (1)
- Semigroup: is a commutative semigroup
- (2)
- Labeling: For all and such that ,
- (3)
- Unit and Null: For all there exist unit and null elements and in such that and for all ψ with . Further, for all , and .
- (4)
- Projection: For all and such that ,
- (5)
- Combination: For all , if and , then
- (6)
- Idempotency: For all and such that ,
- (1)
- Labeling: For , let .
- (2)
- Combination: For with , , combination is defined pointwise for all as
- (3)
- Projection: For with and , the projection is defined for all as
2.3. Transport of Information
- (1)
- If , then ,
- (2)
- If , then ,
- (3)
- ,
- (4)
- .
3. Domain-free Algebras
3.1. Another View
- Combination:Φ is a commutative and idempotent semigroup under the combination operation · with a unit 1 and a null element 0.
- Extraction: Each extraction operator satisfies the following conditions:
- (a)
- ,
- (b)
- for all ,
- (c)
- for all .
- Composition:E is a commutative and idempotent semigroup under ordinary composition of mappings.
3.2. Order
- (1)
- for all ,
- (2)
- implies for all ,
- (3)
- implies for all ,
- (4)
- for all and all ,
- (5)
- .
- (a)
- ,
- (b)
- for all ,
- (c)
- .
3.3. Ideal Completion
- (1)
- , and jointly imply ,
- (2)
- imply .
3.4. Support
- (1)
- , that is, x is a support of ,
- (2)
- implies , that is, if x is a support of ϕ, then x is a also a support of any ,
- (3)
- implies , that is, if x and y are supports of ϕ, then so is ,
- (4)
- implies , that is, if x is a support of ϕ, then is a support of ,
- (5)
- and imply , that is, if x is a support ϕ, then any finer question y is a support of ϕ too,
- (6)
- and imply , that is, if x is a support of ϕ and ψ, then it is a support of too,
- (7)
- If Q is a lattice, then and imply , that is, if x is a support of ϕ, and y a support of ψ, then is a support of .
3.5. Atoms
- (1)
- ,
- (2)
- For all , and jointly imply either or .
- (1)
- If α is an atom on domain x, and , then either or .
- (2)
- If α is an atom on domain x, and , then is an atom on domain y.
- (3)
- If α and β are atoms on domain x, then either or .
- (1)
- A labeled information algebra is called atomic if for all different from the set is not empty, i.e., if every piece of information contains an atom.
- (2)
- A labeled information algebra is called atomistic, if for all different from , ψ is the infimum of the atoms it contains,
- (3)
- A labeled information algebra is called completely atomistic, if it is atomistic and if for all and for every subset of atoms , the infimum exists and belongs to Φ.
- (1)
- If , then .
- (2)
- If , then .
- (3)
- If , then .
- (4)
- If , and , then there exists a γ such that and , .
- (5)
- If and , then there exists a γ such that and .
4. Generic Constructions
4.1. Generalized Relational Algebras
- (1)
- Labeling: , ,
- (2)
- Projection:, , defined for .
- (1)
- If , then ,
- (2)
- If , then ,
- (3)
- If , then ,
- (4)
- If , and , then there exists such that and , ,
- (5)
- If and , then there exists such that and .
- (1)
- Labeling:,
- (2)
- Combination:,
- (3)
- Projection:.
4.2. Quantifier Algebras
- (1)
- ,
- (2)
- ,
- (3)
- .
4.3. Consequence Operators
- (1)
- for all ,
- (2)
- If for all and , then .
- (1)
- ,
- (2)
- ,
- (3)
- if , then .
4.4. Language and Models
- (a)
- ,
- (b)
- ,
- (c)
- .
4.5. Morphisms
5. Compact Algebras
5.1. Finiteness
- (1)
- Subalgebra: The system is a subalgebra of , that is it is closed under combination and extraction and the unit 1 and the null element 0 belong to .
- (2)
- Convergence: If is directed, then the supremum exists in Φ.
- (3)
- Density: For all and ,
- (4)
- Compactness: If is directed, and satisfies , then there is a such that .
5.2. Continuous Maps
- (1)
- Combination: ,
- (2)
- Extraction: .
5.3. Categories of Information Algebras
- (1)
- The category IA has as its objects domain-free information algebras and as its morphisms order preserving maps.
- (2)
- The category CompIA has as its objects compact information algebras and as its morphisms continuous maps.
- (1)
- both have terminal objects,
- (2)
- both have direct products,
- (3)
- both have exponentials.
6. Outlook
Acknowledgments
Author Contribution
Conflicts of Interest
References
- Shenoy, P.P.; Shafer, G. Propagating Belief Functions Using Local Computation. IEEE Expert 1986, 1, 43–52. [Google Scholar] [CrossRef]
- Shenoy, P.P.; Shafer, G. Axioms for Probability and Belief Function Propagation. In Classic Works of the Dempster-Shafer Theory of Belief Functions; Yager, R.R., Liu, L., Eds.; Springer: Berlin/Heidelberg, Germany, 2008; pp. 499–528. [Google Scholar]
- Lauritzen, S.L.; Spiegelhalter, D.J. Local Computations with Probabilities on Graphical Structures and their Application to Expert Systems. J. R. Stat. Soc. Ser. B 1988, 50, 157–224. [Google Scholar]
- Shenoy, P.P. A Valuation-Based Language for Expert Systems. Int. J. Approx. Reason. 1989, 3, 383–411. [Google Scholar] [CrossRef]
- Kohlas, J.; Shenoy, P.P. Computation in Valuation Algebras. In Handbook of Defeasible Reasoning and Uncertainty Management Systems, Volume 5: Algorithms for Uncertainty and Defeasible Reasoning; Kohlas, J., Moral, S., Eds.; Springer: Dordrecht, The Netherlands, 2000; pp. 5–39. [Google Scholar]
- Kohlas, J. Information Algebras: Generic Structures for Inference; Springer: Berlin, Germany, 2003. [Google Scholar]
- Pouly, M.; Kohlas, J. Generic Inference. A Unified Theory for Automated Reasoning; Wiley: Hoboken, NJ, USA, 2011. [Google Scholar]
- Kohlas, J.; Schmid, J. Research Notes: An Algebraic Theory of Information; Technical Report 06-03; Department of Informatics, University of Fribourg: Fribourg, Switzerland, 2013; Available online: http://diuf.unifr.ch/drupal/tns/sites/diuf.unifr.ch.drupal.tns/files/file/main_0.pdf (accessed on 9 April 2014).
- Kohlas, J.; Schneuwly, C. Information Algebra. In Formal Theories of Information: From Shannon to Semantic Information Theory and General Concepts of Information; Sommaruga, G., Ed.; Lecture Notes in Computer Science, Volume 5363; Springer: Berlin, Germany, 2009; pp. 95–127. [Google Scholar]
- Grätzer, G. General Lattice Theory; Academic Press: London, UK, 1978. [Google Scholar]
- Kohlas, J.; Wilson, N. Semiring Induced Valuation Algebras: Exact and Approximate Local Computation Algorithms. Artif. Intell. 2008, 172, 1360–1399. [Google Scholar] [CrossRef]
- Cignoli, R. Quantifiers on Distributive Lattices. Discret. Math. 1991, 96, 183–197. [Google Scholar] [CrossRef]
- Halmos, P.R.; Givant, S. Logic as Algebra; Dolciani Mathematical Expositions Book 21; The Mathematical Association of America: Washington, DC, USA, 1998. [Google Scholar]
- Davey, B.; Priestley, H. Introduction to Lattices and Order; Cambridge University Press: Cambridge, UK, 1990. [Google Scholar]
- Halmos, P.R. Algebraic Logic; Chelsea: New York, NY, USA, 1962. [Google Scholar]
- Plotkin, B. Universal Algebra, Algebraic Logic, and Databases; Mathematics and its applications; Springer: Dordrecht, The Netherlands, 1994; Volume 272. [Google Scholar]
- Henkin, L.; Monk, J.D.; Tarski, A. Cylindric Algebras; North-Holland: Amsterdam, The Netherlands, 1971. [Google Scholar]
- Kohlas, J.; Staerk, R. Information Algebras and Consequence Operators. Log. Universalis 2007, 1, 1139–1165. [Google Scholar] [CrossRef]
- Wilson, N.; Mengin, J. Logical Deduction Using the Local Computation Framework. In Proceedings of European Conference on Symbolic and Quantitative Approaches to Reasoning and Uncertainty, ECSQARU’99, London, UK, 5–9 July 1999; pp. 386–396.
- Barwise, J.; Seligman, J. Information Flow: The Logic of Distributed Systems; Number 44 in Cambridge Tracts in Theoretical Computer Science; Cambridge University Press: Cambridge, UK, 1997. [Google Scholar]
- Ganter, B.; Wille, R. Formal Concept Analysis; Translated to English by C. Franzke; Springer: Berlin, Germany, 1999. [Google Scholar]
- Langel, J. Logic and Information: A Unifying Approach to Semantic Information Theory. Ph.D. Thesis, University of Fribourg, Fribourg, Switzerland, 2010. [Google Scholar]
- Bar-Hillel, Y.; Carnap, R. An Outline of a Theory of Semantic Information; Technical Report 247; Research Laboratory of Electronics, Massachusetts Institute of Technology: Cambridge, MA, USA, 1952. [Google Scholar]
- Bar-Hillel, Y.; Carnap, R. Semantic Information. Br. J. Philos. Sci. 1953, 4, 147–157. [Google Scholar] [CrossRef]
- Bar-Hillel, Y. Language and Information: Selected Essays on Their Theory and Application; Addison-Wesley: Boston, MA, USA, 1964. [Google Scholar]
- Hintikka, J. On Semantic Information. In Physics, Logic, and History, Proceedings of the First International Colloquium, Denver, CO, USA, 16–20 May 1966; Hintikka, J., Suppes, P., Eds.; Springer: New York, NY, USA, 1970; pp. 3–27. [Google Scholar]
- Hintikka, J. Surface Information and Depth Information. In Information and Inference; Hintikka, J., Suppes, P., Eds.; Springer: Dordrecht, The Netherlands, 1970; pp. 263–297. [Google Scholar]
- Hintikka, J. The Semantics of Questions and the Questions of Semantics; Volume 28, Acta Philosophica Fennica; North-Holland: Amsterdam, The Netherlands, 1976. [Google Scholar]
- Hintikka, J. Answers to Questions. In Questions; Hiz, H., Ed.; D. Reidel: Dordrecht, The Netherlands, 1978; pp. 279–300. [Google Scholar]
- Scott, D.S. Outline of a Mathematical Theory of Computation; Technical Monograph PRG-2; Oxford University Computing Laboratory, Programming Research Group: Oxford, UK, 1970. [Google Scholar]
- Scott, D.S. Continuous Lattices. In Toposes, Algebraic Geometry and Logic; Lecture Notes in Mathematics; Springer: Berlin/Heidelberg, Germany, 1972; pp. 97–136. [Google Scholar]
- Scott, D.S. Domains for Denotational Semantics. In Automata, Languages and Programming; Nielsen, M., Schmitt, E.M., Eds.; Springer: Berlin/Heidelberg, Germany, 1982; pp. 577–610. [Google Scholar]
- Scott, D.S. Computer Science Department, Carnegie Mellon University, PA, USA. A New Category? Domains, Spaces and Equivalence Relations. Unpublished manuscript. 1996. [Google Scholar]
- Guan, X.; Li, Y. On Two Types of Continuous Information Algebras. Int. J. Uncertain. Fuzziness Knowl.-Based Syst. 2012, 20, 655–671. [Google Scholar] [CrossRef]
- Stoltenberg-Hansen, V.; Lindstroem, I.; Griftor, E. Mathematical Theory of Domains; Cambridge University Press: Cambridge, UK, 1994. [Google Scholar]
- Burgin, M. Theory of Information: Fundamentality, Diversity and Unification; World Scientific: Hackensack, NJ, USA, 2010. [Google Scholar]
- Groenendijk, J.; Stokhof, M. Studies on the Semantics of Questions and the Pragmatics of Answers. Ph.D. Thesis, Universiteit van Amsterdam, Amsterdam, The Netherlands, 1984. [Google Scholar]
- Groenendijk, J.; Stokhof, M. Questions. In Handbook of Logic and Language, 2nd ed.; van Benthem, J., ter Meulen, A., Eds.; Elsevier: London, UK, 2010; Chapter 25; pp. 1059–1131. [Google Scholar]
- Groenendijk, J. Questions and answers: Semantics and logic. In Proceedings of the 2nd CologNET-ElsET Symposium, Questions and Answers: Theoretical and Applied Perspectives. Amsterdam, The Netherlands, 18 December 2003; pp. 12–23.
- Groenendijk, J. The Logic of Interrogation: Classical Version. In Proceedings of the Ninth Conference on Semantic and Linguistic Theory, Santa Cruz, CA, USA, 19–21 February 1999; pp. 109–126.
- Hintikka, J. Questions about Questions. In Semantics and Philosophy; Munitz, M., Unger, P., Eds.; New York University Press: New York, NY, USA, 1974; pp. 103–158. [Google Scholar]
- Van Rooij, R. Comparing Questions and Answers: A Bit of Logic, a Bit of Language and Some Bits of Information. Available online: http://staff.science.uva.nl/ vanrooy/Sources.pdf (accessed on 8 April 2014).
- Barwise, J.; Seligman, J. Information Flow: The Logic of Distributed Systems; Cambridge University Press: Cambridge, UK, 1997. [Google Scholar]
- Shannon, C. A Mathematical Theory of Communications. Bell Syst. Tech. J. 1948, 27, 379–432. [Google Scholar] [CrossRef]
- Kolmogorov, A.N. Three Approaches to the Quantitative Definition of Information. Int. J. Comput. Math. 1968, 2, 1–4. [Google Scholar] [CrossRef]
- Kolmogorov, A.N. Logical Basis for information Theory and Probability. IEEE Trans. Inf. Theory 1968, 14, 662–664. [Google Scholar] [CrossRef]
- Chaitin, G. Algorithmic Information Theory; Cambridge University Press: Cambridge, UK, 1987. [Google Scholar]
- Li, M.; Vitanyi, P. An introduction to Kolmogorov complexity and its applications; Springer: New York, NY, USA, 1993. [Google Scholar]
- Hartley, R. Transmission of Information. Bell Syst. Tech. J. 1928, 535–563. [Google Scholar] [CrossRef]
- Cowell, R.G.; Dawid, A.P.; Lauritzen, S.L.; Spiegelhalter, D.J. Probabilistic Networks and Expert Systems: Exact Computational Methods for Bayesian Networks; Springer: Berlin/Heidelberg, Germany, 1999. [Google Scholar]
- Dawid, A.P. Separoids: A Mathematical Framework for Conditional Independence and Irrelevance. Ann. Math. Artif. Intell. 2001, 32, 335–372. [Google Scholar] [CrossRef]
- Maier, D. The Theory of Relational Databases; Pitman: London, UK, 1983. [Google Scholar]
- Beeri, C.; Fagin, R.; Maier, D.; Yannakakis, M. On the Desirability of Acyclic Database Schemes. J. ACM 1983, 30, 479–513. [Google Scholar] [CrossRef]
- Studeny, M. Formal Properties of Conditional Independence in Different Calculi of AI. In Symbolic and Quantitative Approaches to Reasoning and Uncertainty; Clarke, M., Kruse, R., Moral, S., Eds.; Lecture Notes in Computer Science; Springer: Berlin, Germany, 1993; Volume 747, pp. 341–348. [Google Scholar]
- Shenoy, P. Conditional Independence in Valuation-based Systems. Int. J. Approx. Reason. 1994, 10, 203–234. [Google Scholar] [CrossRef]
- Kohlas, J.; Eichenberger, C. Uncertain Information. In Formal Theories of Information: From Shannon to Semantic Information Theory and General Concepts of Information; Sommaruga, G., Ed.; Lecture Notes in Computer Science, Volume 5363; Springer: Berlin, Germany, 2009; pp. 128–160. [Google Scholar]
- Choquet, G. Theory of Capacities. Annales de l’Institut Fourier 1953–1954, 5, 131–295. [Google Scholar] [CrossRef]
- Choquet, G. Lectures on Analysis; Benjaminm: New York, NY, USA, 1969. [Google Scholar]
- Kohlas, J. Support-and Plausibility Functions Induced by Filter-Valued Mappings. Int. J. Gen. Syst. 1993, 21, 343–363. [Google Scholar] [CrossRef]
- Dempster, A. Upper and Lower Probabilities Induced by a Multivalued Mapping. Ann. Math. Stat. 1967, 38, 325–339. [Google Scholar] [CrossRef]
- Shafer, G. A Mathematical Theory of Evidence; Princeton University Press: Princeton, NJ, USA, 1976. [Google Scholar]
- Shafer, G. Allocations of Probability. Ann. Prob. 1979, 7, 827–839. [Google Scholar] [CrossRef]
- Kohlas, J.; Monney, P. A Mathematical Theory of Hints: An Approach to the Dempster-Shafer Theory of Evidence; Volume 425, Lecture Notes in Economics and Mathematical Systems; Springer: Berlin/Heidelberg, Germany, 1995. [Google Scholar]
- Haenni, R.; Kohlas, J.; Lehmann, N. Probabilistic Argumentation Systems. In Handbook of Defeasible Reasoning and Uncertainty Management Systems, Volume 5: Algorithms for Uncertainty and Defeasible Reasoning; Kohlas, J., Moral, S., Eds.; Springer: Dordrecht, The Netherlands, 2000; pp. 221–287. [Google Scholar]
- Pouly, M.; Kohlas, J.; Ryan, P. Generalized Information Theory for Hints. Int. J. Approx. Reason. 2013, 54, 17–34. [Google Scholar] [CrossRef]
- Gierz, E.G. Continuous Lattices and Domains; Cambridge University Press: Cambridge, UK, 2003. [Google Scholar]
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Kohlas, J.; Schmid, J. An Algebraic Theory of Information: An Introduction and Survey. Information 2014, 5, 219-254. https://doi.org/10.3390/info5020219
Kohlas J, Schmid J. An Algebraic Theory of Information: An Introduction and Survey. Information. 2014; 5(2):219-254. https://doi.org/10.3390/info5020219
Chicago/Turabian StyleKohlas, Juerg, and Juerg Schmid. 2014. "An Algebraic Theory of Information: An Introduction and Survey" Information 5, no. 2: 219-254. https://doi.org/10.3390/info5020219
APA StyleKohlas, J., & Schmid, J. (2014). An Algebraic Theory of Information: An Introduction and Survey. Information, 5(2), 219-254. https://doi.org/10.3390/info5020219