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Inference Systems for Inconsistent Information: logical foundations
Inference Systems for Inconsistent Information: logical foundations

A Project coordinated by IIIA.

Web page:

Principal investigator: 

Collaborating organisations:

Universitat de Lleida

Universitat de Lleida

Funding entity:

Ministerio de Ciencia e Innovación
Ministerio de Ciencia e Innovación

Funding call:

Funding call URL:

Project #:

PID2019-111544GB-C21
PID2019-111544GB-C21

Total funding amount:

93.533,00€
93.533,00€

IIIA funding amount:

Duration:

01/Jun/2020
01/Jun/2020
31/May/2023
31/May/2023

Extension date:

In this project the main goal is to advance the state-of-the-art in inconsistency-tolerant inference models in different scenarios: MaxSAT techniques in classical and many-valued logics, non classical graded logics, argumentation frameworks, both in theoretic and practical aspects, and in their application to the analysis of discussions in social networks. The main difficulty we want to tackle is the existence of inconsistency in knowledge bases, a common property in knowledge bases that come from real applications, specially when the information is obtained as the aggregation of information coming from different sources.

On the one hand, we plan to use extensions of different non-classical logics, mainly based on fuzzy logics and modal fuzzy logics, for being able to extract useful information from such kind of knowledge bases, and being able to manage both uncertain and inconsistent information. We will define models over these expanded logics, as well as inference algorithms that can be used to extract useful information under these new logics. The algorithms studied will be either ad-hoc or based on SAT/MaxSAT reductions.

On the other hand, we also plan to consider an approach for working with inconsistent information based on extensions of argumentation models, incorporating again both uncertain and inconsistent information. We will define argumentation models and algorithms for them, trying to identify special cases that can be solver with efficient algorithms. We also plan to study approximate inference algorithms for these problems, based on machine learning methods.

As an application domain, we plan to test our models and algorithms on different problems related to the analysis of discussions and comment threads in different social networks, where inconsistency is a very common property in these scenarios, but we may also encounter uncertain information, as not all the pieces of information we find in them are always believed to have the same strength.

The first subproject will mostly focus on the theoretical aspects of the project and its main activity will be the definition of new logical formalisms and inference systems to deal with inconsistencies in different scenarios. Some of the theoretical problems we propose are motivated by our experience in the development of proof procedures and the resolution of challenging combinatorial optimization problems.

In this project the main goal is to advance the state-of-the-art in inconsistency-tolerant inference models in different scenarios: MaxSAT techniques in classical and many-valued logics, non classical graded logics, argumentation frameworks, both in theoretic and practical aspects, and in their application to the analysis of discussions in social networks. The main difficulty we want to tackle is the existence of inconsistency in knowledge bases, a common property in knowledge bases that come from real applications, specially when the information is obtained as the aggregation of information coming from different sources.

On the one hand, we plan to use extensions of different non-classical logics, mainly based on fuzzy logics and modal fuzzy logics, for being able to extract useful information from such kind of knowledge bases, and being able to manage both uncertain and inconsistent information. We will define models over these expanded logics, as well as inference algorithms that can be used to extract useful information under these new logics. The algorithms studied will be either ad-hoc or based on SAT/MaxSAT reductions.

On the other hand, we also plan to consider an approach for working with inconsistent information based on extensions of argumentation models, incorporating again both uncertain and inconsistent information. We will define argumentation models and algorithms for them, trying to identify special cases that can be solver with efficient algorithms. We also plan to study approximate inference algorithms for these problems, based on machine learning methods.

As an application domain, we plan to test our models and algorithms on different problems related to the analysis of discussions and comment threads in different social networks, where inconsistency is a very common property in these scenarios, but we may also encounter uncertain information, as not all the pieces of information we find in them are always believed to have the same strength.

The first subproject will mostly focus on the theoretical aspects of the project and its main activity will be the definition of new logical formalisms and inference systems to deal with inconsistencies in different scenarios. Some of the theoretical problems we propose are motivated by our experience in the development of proof procedures and the resolution of challenging combinatorial optimization problems.

In Press
Tommaso Flaminio,  Lluís Godo,  Paula Menchón,  & Ricardo Oscar Rodríguez (In Press). Algebras and relational frames for Gödel modal logic and some of its extensions. M. Coniglio, E. Koubychkina, & D. Zaitsev (Eds.), Many-valued Semantics and Modal Logics: Essays in Honour of Yuriy Vasilievich Ivlev. Springer (Also as CoRR, abs/2110.02528. https://doi.org/http://arxiv.org/abs/2110.02528). [BibTeX]  [PDF]
2022
Juan C. L. Teze,  Lluís Godo,  & Gerardo I. Simari (2022). An Approach to Improve Argumentation-Based Epistemic Planning with Contextual Preferences. International Journal of Approximate Reasoning, 151, 130-163. https://doi.org/10.1016/j.ijar.2022.09.005. [BibTeX]  [PDF]
Tommaso Flaminio,  Angelo Gilio,  Lluís Godo,  & Giuseppe Sanfilippo (2022). Canonical Extensions of Conditional Probabilities and Compound Conditionals. Davide Ciucci al. (Eds.), 17th Intl. Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems (IPMU 2022) (pp. 584--597). Springer International Publishing. https://doi.org/10.1007/978-3-031-08974-9_47. [BibTeX]  [PDF]
Tommaso Flaminio,  Angelo Gilio,  Lluís Godo,  & Giuseppe Sanfilippo (2022). Compound conditionals as random quantities and Boolean algebras. Principles of Knowledge Representation and Reasoning - 19th International Conference, KR 2022, Haifa, Israel (pp. 141-151). [BibTeX]  [PDF]
Marcelo Coniglio,  Francesc Esteva,  Tommaso Flaminio,  & Lluís Godo (2022). On the expressive power of Lukasiewicz’s square operator. Journal of Logic and Computation, 32, 767-807. https://doi.org/10.1093/logcom/exab064. [BibTeX]  [PDF]
2021
Tommaso Flaminio,  & Lluís Godo (2021). A fuzzy probability logic for compound conditionals. XX Spanish Congress on Fuzzy Logic and Technologies (ESTYLF 20/21), Actas CAEPIA 20/21 (pp. 256-261). [BibTeX]  [PDF]
Tommaso Flaminio,  Lluís Godo,  Paula Menchón,  & Ricardo Oscar Rodríguez (2021). Algebras and relational frames for Godel modal logic and some of its extensions. CoRR, abs/2110.02528. https://doi.org/http://arxiv.org/abs/2110.02528. [BibTeX]  [PDF]
Juan Carlos Teze,  & Lluís Godo (2021). An Architecture for Argumentation-based Epistemic Planning: A First Approach with Contextual Preferences. IEEE Intelligent Systems, 36, 43-51. https://doi.org/10.1109/MIS.2020.3028833. [BibTeX]  [PDF]
Tommaso Flaminio,  Lluís Godo,  & Sara Ugolini (2021). Canonical Extension of Possibility Measures to Boolean Algebras of Conditionals. Jirina Vejnarová, & Nic Wilson (Eds.), Symbolic and Quantitative Approaches to Reasoning with Uncertainty - 16th European Conference, ECSQARU 2021, Prague, Czech Republic, September 21-24, 2021, Proceedings (pp. 543--556). Springer. https://doi.org/10.1007/978-3-030-86772-0_39. [BibTeX]  [PDF]
Marcelo Coniglio,  Francesc Esteva,  Joan Gispert,  & Lluís Godo (2021). Degree-preserving Gödel logics with an involution: intermediate logics and (ideal) paraconsistency. O. Arielli, & A. Zamansky (Eds.), Arnon Avron on Semantics and Proof Theory of Non-Classical Logics (pp 107--139). Springer. https://doi.org/10.1007/978-3-030-71258-7_6. [BibTeX]  [PDF]
Stefano Bonzio,  Gustavo Cevolani,  & Tommaso Flaminio (2021). How to Believe Long Conjunctions of Beliefs: Probability, Quasi-Dogmatism and Contextualism. Erkenntnis. https://doi.org/10.1007/s10670-021-00389-7. [BibTeX]  [PDF]
Francesc Esteva,  Aldo Figallo-Orellano,  Tommaso Flaminio,  & Lluís Godo (2021). Logics of formal inconsistency based on distributive involutive residuated lattices. Journal of Logic and Computation, 31, 1226-1265. https://doi.org/10.1093/logcom/exab029. [BibTeX]  [PDF]
Pilar Dellunde,  Lluís Godo,  & Amanda Vidal (2021). On probabilistic logical argumentation based on conditional probability. M. Villaret al. (Eds.), Artificial Intelligence Research and Development - CCIA 2021, Lleida, Spain, October 20-22, 2021, Proceedings (pp. 7--16). IOS Press. https://doi.org/10.3233/FAIA210111. [BibTeX]
Tommaso Flaminio (2021). On standard completeness and finite model property for a probabilistic logic on Łukasiewicz events. Int. J. Approx. Reason., 131, 136--150. https://doi.org/10.1016/j.ijar.2020.12.023. [BibTeX]  [PDF]
Tommaso Flaminio,  Lluís Godo,  Paula Menchón,  & Ricardo Rodriguez (2021). On the role of Dunn and Fisher Servi axioms in relational frames for Godel modal logics. Third International Conference on Non-Classical Modal and Predicate Logics (NCMPL 2021) - Book of Abstracts (pp. 52-54). Ruhr University Bochum. [BibTeX]  [PDF]
Esther Anna Corsi,  Tommaso Flaminio,  & Hykel Hosni (2021). Scoring Rules for Belief Functions and Imprecise Probabilities: A Comparison. Jirina Vejnarová, & Nic Wilson (Eds.), Symbolic and Quantitative Approaches to Reasoning with Uncertainty - 16th European Conference, ECSQARU 2021, Prague, Czech Republic, September 21-24, 2021, Proceedings (pp. 301--313). Springer. https://doi.org/10.1007/978-3-030-86772-0_22. [BibTeX]  [PDF]
Francesc Esteva,  Aldo Figallo-Orellano,  Tommaso Flaminio,  & Lluís Godo (2021). Some Categorical Equivalences for Nelson Algebras with Consistency Operators. Joint Proceedings of the 19th World Congress of the International Fuzzy Systems Association (IFSA), the 12th Conference of the European Society for Fuzzy Logic and Technology (EUSFLAT), and the 11th International Summer School on Aggregation Operators (AGOP) (pp. 420-426). Atlantis Press. https://doi.org/10.2991/asum.k.210827.056. [BibTeX]  [PDF]
Esther Anna Corsi,  Tommaso Flaminio,  & Hykel Hosni (2021). When Belief Functions and Lower Probabilities are Indistinguishable. A. Cano, J. De Bock, E. Miranda, & S. Moral (Eds.), Proceedings of the Twelveth International Symposium on Imprecise Probability: Theories and Applications (pp. 83--89). Proceedings of Machine Learning Research 147. [BibTeX]  [PDF]
2002
Ricardo Rodriguez,  Olym Tuyt,  Francesc Esteva,  & Lluís Godo (2002). Simplified Kripke semantics for K45-like Godel modal logics and its axiomatic extensions. Studia Logica. https://doi.org/10.1007/s11225-022-09987-0. [BibTeX]  [PDF]
Eva Armengol
Tenured Scientist
Phone Ext. 431851

Pilar Dellunde
Adjunct Scientist
Phone Ext. 431850

Francesc Esteva
Adjunct Professor Ad Honorem
Phone Ext. 431827

Tommaso Flaminio
Tenured Scientist
Phone Ext. 431841

Angel García-Cerdaña
Adjunct Scientist
Lluís Godo
Research Professor
Phone Ext. 431857

Felip Manyà
Tenured Scientist
Phone Ext. 431854

Pedro Meseguer
Scientific Researcher
Phone Ext. 431862

Amanda Vidal
Contract Researcher
Phone Ext. 431844