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2023
Journal article
Open Access
Situated conditional reasoning
Casini G., Meyer T., Varzinczak I.
Conditionals are useful for modelling many forms of everyday human reasoning but are not always sufficiently expressive to represent the information we want to reason about. In this paper, we make a case for a form of situated conditional. By 'situated', we mean that there is a context, based on an agent's beliefs and expectations, that works as background information in evaluating a conditional, and we allow such a context to vary. These conditionals are able to distinguish, for example, between expectations and counterfactuals. Formally, they are shown to generalise the conditional setting in the style of Kraus, Lehmann, and Magidor. We show that situated conditionals can be described in terms of a set of rationality postulates. We then propose an intuitive semantics for these conditionals and present a representation result which shows that our semantic construction corresponds exactly to the description in terms of postulates. With the semantics in place, we define a form of entailment for situated conditional knowledge bases, which we refer to as minimal closure. Finally, we proceed to show that it is possible to reduce the computation of minimal closure to a series of propositional entailment and satisfiability checks. While this is also the case for rational closure, it is somewhat surprising that the result carries over to minimal closure.Source: Artificial intelligence (Gen. ed.) 319 (2023). doi:10.1016/j.artint.2023.103917
DOI: 10.1016/j.artint.2023.103917
DOI: 10.48550/arxiv.2109.01552
Project(s): TAILOR
Metrics:
Casini G., Meyer T., Varzinczak I.
Conditionals are useful for modelling many forms of everyday human reasoning but are not always sufficiently expressive to represent the information we want to reason about. In this paper, we make a case for a form of situated conditional. By 'situated', we mean that there is a context, based on an agent's beliefs and expectations, that works as background information in evaluating a conditional, and we allow such a context to vary. These conditionals are able to distinguish, for example, between expectations and counterfactuals. Formally, they are shown to generalise the conditional setting in the style of Kraus, Lehmann, and Magidor. We show that situated conditionals can be described in terms of a set of rationality postulates. We then propose an intuitive semantics for these conditionals and present a representation result which shows that our semantic construction corresponds exactly to the description in terms of postulates. With the semantics in place, we define a form of entailment for situated conditional knowledge bases, which we refer to as minimal closure. Finally, we proceed to show that it is possible to reduce the computation of minimal closure to a series of propositional entailment and satisfiability checks. While this is also the case for rational closure, it is somewhat surprising that the result carries over to minimal closure.Source: Artificial intelligence (Gen. ed.) 319 (2023). doi:10.1016/j.artint.2023.103917
DOI: 10.1016/j.artint.2023.103917
DOI: 10.48550/arxiv.2109.01552
Project(s): TAILOR
Metrics:
See at:
arXiv.org e-Print Archive 
| ISTI Repository | Artificial Intelligence 
| doi.org | www.sciencedirect.com | CNR ExploRA
2023
Journal article
Open Access
Defeasible RDFS via rational closure
Casini G., Straccia U.
In the field of non-monotonic logics, the notion of Rational Closure (RC) is acknowledged as a notable approach. In recent years, RC has gained popularity in the context of Description Logics (DLs), the logic underpinning the standard semantic Web Ontology Language OWL 2, whose main ingredients are classes, the relationship among classes and roles, which are used to describe the properties of classes. In this work, we show instead how to integrate RC within the triple language RDFS (Resource Description Framework Schema), which together with OWL 2 is a major standard semantic web ontology language. To do so, we start from rdf, a minimal, but significant RDFS fragment that covers the essential features of RDFS, and then extend it to rdf_\bot, allowing to state that two entities are incompatible/disjoint with each other. Eventually, we propose defeasible rdf_\bot via a typical RC construction allowing to state default class/property inclusions. Furthermore, to overcome the main weaknesses of RC in our context, i.e., the "drowning problem" (viz. the "inheritance blocking problem"), we further extend our construction by leveraging Defeasible Inheritance Networks (DIN) defining a new non-monotonic inference relation that combines the advantages of both (RC and DIN). To the best of our knowledge this is the first time of such an attempt. In summary, the main features of our approach are: (i) the defeasible rdf_\bot we propose here remains syntactically a triple language by extending it with new predicate symbols with specific semantics; (ii) the logic is defined in such a way that any RDFS reasoner/store may handle the new predicates as ordinary terms if it does not want to take account of the extra non-monotonic capabilities; (iii) the defeasible entailment decision procedure is built on top of the rdf_\bot entailment decision procedure, which in turn is an extension of the one for rdf via some additional inference rules favouring a potential implementation; (iv) the computational complexity of deciding entailment in rdf and rdf_\bot are the same; and (v) defeasible entailment can be decided via a polynomial number of calls to an oracle deciding ground triple entailment in rdf_\bot and, in particular, deciding defeasible entailment can be done in polynomial time.Source: Information sciences 643 (2023). doi:10.1016/j.ins.2022.11.165
DOI: 10.1016/j.ins.2022.11.165
DOI: 10.48550/arxiv.2007.07573
Project(s): TAILOR
Metrics:
Casini G., Straccia U.
In the field of non-monotonic logics, the notion of Rational Closure (RC) is acknowledged as a notable approach. In recent years, RC has gained popularity in the context of Description Logics (DLs), the logic underpinning the standard semantic Web Ontology Language OWL 2, whose main ingredients are classes, the relationship among classes and roles, which are used to describe the properties of classes. In this work, we show instead how to integrate RC within the triple language RDFS (Resource Description Framework Schema), which together with OWL 2 is a major standard semantic web ontology language. To do so, we start from rdf, a minimal, but significant RDFS fragment that covers the essential features of RDFS, and then extend it to rdf_\bot, allowing to state that two entities are incompatible/disjoint with each other. Eventually, we propose defeasible rdf_\bot via a typical RC construction allowing to state default class/property inclusions. Furthermore, to overcome the main weaknesses of RC in our context, i.e., the "drowning problem" (viz. the "inheritance blocking problem"), we further extend our construction by leveraging Defeasible Inheritance Networks (DIN) defining a new non-monotonic inference relation that combines the advantages of both (RC and DIN). To the best of our knowledge this is the first time of such an attempt. In summary, the main features of our approach are: (i) the defeasible rdf_\bot we propose here remains syntactically a triple language by extending it with new predicate symbols with specific semantics; (ii) the logic is defined in such a way that any RDFS reasoner/store may handle the new predicates as ordinary terms if it does not want to take account of the extra non-monotonic capabilities; (iii) the defeasible entailment decision procedure is built on top of the rdf_\bot entailment decision procedure, which in turn is an extension of the one for rdf via some additional inference rules favouring a potential implementation; (iv) the computational complexity of deciding entailment in rdf and rdf_\bot are the same; and (v) defeasible entailment can be decided via a polynomial number of calls to an oracle deciding ground triple entailment in rdf_\bot and, in particular, deciding defeasible entailment can be done in polynomial time.Source: Information sciences 643 (2023). doi:10.1016/j.ins.2022.11.165
DOI: 10.1016/j.ins.2022.11.165
DOI: 10.48550/arxiv.2007.07573
Project(s): TAILOR
Metrics:
See at:
arXiv.org e-Print Archive | Information Sciences | doi.org | www.sciencedirect.com | CNR ExploRA
2023
Conference article
Open Access
Revising typical beliefs: one revision to rule them all
Heyninck J., Casini G., Meyer T., Straccia U.
Propositional Typicality Logic (PTL) extends propositional logic with a connective $\bullet$ expressing the most typical (alias normal or conventional) situations in which a given sentence holds. As such, it generalises e.g. preferential logics that formalise reasoning with conditionals such as "birds typically fly". In this paper we study the revision of sets of PTL sentences. We first show why it is necessary to extend the PTL language with a possibility operator and then define the revision of PTL sentences syntactically and characterise it semantically. We show that this allows us to represent a wide variety of existing revision methods, such as propositional revision and revision of epistemic states. Furthermore, we provide several examples showing why our approach is innovative. In more detail, we study the revision of a set of conditionals under preferential closure and the addition and contraction of possible worlds from an epistemic state.Source: KR2023 - International Conference on Principles of Knowledge Representation and Reasoning, pp. 355–364, Rhodes, Greece, 2-8/09/2023
DOI: 10.24963/kr.2023/35
Project(s): TAILOR
Metrics:
Heyninck J., Casini G., Meyer T., Straccia U.
Propositional Typicality Logic (PTL) extends propositional logic with a connective $\bullet$ expressing the most typical (alias normal or conventional) situations in which a given sentence holds. As such, it generalises e.g. preferential logics that formalise reasoning with conditionals such as "birds typically fly". In this paper we study the revision of sets of PTL sentences. We first show why it is necessary to extend the PTL language with a possibility operator and then define the revision of PTL sentences syntactically and characterise it semantically. We show that this allows us to represent a wide variety of existing revision methods, such as propositional revision and revision of epistemic states. Furthermore, we provide several examples showing why our approach is innovative. In more detail, we study the revision of a set of conditionals under preferential closure and the addition and contraction of possible worlds from an epistemic state.Source: KR2023 - International Conference on Principles of Knowledge Representation and Reasoning, pp. 355–364, Rhodes, Greece, 2-8/09/2023
DOI: 10.24963/kr.2023/35
Project(s): TAILOR
Metrics:
See at:
ISTI Repository | proceedings.kr.org | CNR ExploRA
2023
Report
Unknown
InfraScience research activity report 2023
Artini M., Assante M., Atzori C., Baglioni M., Bardi A., Bosio C., Bove P., Calanducci A., Candela L., Casini G., Castelli D., Cirillo R., Coro G., De Bonis M., Debole F., Dell'Amico A., Frosini L., Ibrahim A. S. T., La Bruzzo S., Lelii L., Manghi P., Mangiacrapa F., Mangione D., Mannocci A., Molinaro E., Pagano P., Panichi G., Paratore M. T., Pavone G., Piccioli T., Sinibaldi F., Straccia U., Vannini G. L.
InfraScience is a research group of the National Research Council of Italy - Institute of Information Science and Technologies (CNR - ISTI) based in Pisa, Italy. This report documents the research activity performed by this group in 2023 to highlight the major results. In particular, the InfraScience group engaged in research challenges characterising Data Infrastructures, e-Science, and Intelligent Systems. The group activity is pursued by closely connecting research and development and by promoting and supporting open science. In fact, the group is leading the development of two large scale infrastructures for Open Science, i.e. D4Science and OpenAIRE. During 2023 InfraScience members contributed to the publishing of several papers, to the research and development activities of several research projects (primarily funded by EU), to the organization of conferences and training events, to several working groups and task forces.Source: ISTI Annual Reports, 2023
DOI: 10.32079/isti-ar-2023/002
Project(s): Blue Cloud, EOSC Future , TAILOR
Metrics:
Artini M., Assante M., Atzori C., Baglioni M., Bardi A., Bosio C., Bove P., Calanducci A., Candela L., Casini G., Castelli D., Cirillo R., Coro G., De Bonis M., Debole F., Dell'Amico A., Frosini L., Ibrahim A. S. T., La Bruzzo S., Lelii L., Manghi P., Mangiacrapa F., Mangione D., Mannocci A., Molinaro E., Pagano P., Panichi G., Paratore M. T., Pavone G., Piccioli T., Sinibaldi F., Straccia U., Vannini G. L.
InfraScience is a research group of the National Research Council of Italy - Institute of Information Science and Technologies (CNR - ISTI) based in Pisa, Italy. This report documents the research activity performed by this group in 2023 to highlight the major results. In particular, the InfraScience group engaged in research challenges characterising Data Infrastructures, e-Science, and Intelligent Systems. The group activity is pursued by closely connecting research and development and by promoting and supporting open science. In fact, the group is leading the development of two large scale infrastructures for Open Science, i.e. D4Science and OpenAIRE. During 2023 InfraScience members contributed to the publishing of several papers, to the research and development activities of several research projects (primarily funded by EU), to the organization of conferences and training events, to several working groups and task forces.Source: ISTI Annual Reports, 2023
DOI: 10.32079/isti-ar-2023/002
Project(s): Blue Cloud
, EOSC Future , TAILOR Metrics:
See at: CNR ExploRA
2023
Contribution to conference
Open Access
Preface for the first Workshop on AI-driven heterogeneous data management: Completing, merging, handling inconsistencies and query-answering (ENIGMA-2023)
Benferhat S., Casini G., Meyer T., Tettamanzi A. G. B.
Proceedings of 1st Workshop on AI-driven heterogeneous data management: Completing, merging, handling inconsistencies and query-answering, co-located with 20th International Conference on Principles of Knowledge Representation and Reasoning (KR 2023).Source: Aachen: CEUR-WS.org, 2023
Benferhat S., Casini G., Meyer T., Tettamanzi A. G. B.
Proceedings of 1st Workshop on AI-driven heterogeneous data management: Completing, merging, handling inconsistencies and query-answering, co-located with 20th International Conference on Principles of Knowledge Representation and Reasoning (KR 2023).Source: Aachen: CEUR-WS.org, 2023
See at:
ceur-ws.org | ISTI Repository | CNR ExploRA
2022
Conference article
Open Access
A rational entailment for expressive description logics via description logic programs
Casini G., Straccia U.
Lehmann and Magidor's rational closure is acknowledged as a land-mark in the field of non-monotonic logics and it has also been re-formulated in the context ofDescription Logics (DLs). We show here how to model a rational form of entailment for expressive DLs, such as SROIQ, providing a novel reasoning procedure that compiles a non-monotone DL knowledge base into a description logic program(dl-program).Source: SACAIR 2021 - Second Southern African Conference, pp. 177–191, Durban, South Africa, 6-10/12/2021
DOI: 10.1007/978-3-030-95070-5_12
Metrics:
Casini G., Straccia U.
Lehmann and Magidor's rational closure is acknowledged as a land-mark in the field of non-monotonic logics and it has also been re-formulated in the context ofDescription Logics (DLs). We show here how to model a rational form of entailment for expressive DLs, such as SROIQ, providing a novel reasoning procedure that compiles a non-monotone DL knowledge base into a description logic program(dl-program).Source: SACAIR 2021 - Second Southern African Conference, pp. 177–191, Durban, South Africa, 6-10/12/2021
DOI: 10.1007/978-3-030-95070-5_12
Metrics:
See at:
ISTI Repository | link.springer.com | CNR ExploRA
2022
Report
Open Access
A general framework for modelling conditional reasoning - Preliminary report
Casini G., Straccia U.
We introduce and investigate here a formalisation for conditionals that allows the definition of a broad class of reasoning systems. This framework covers the most popular kinds of conditional reasoning in logic-based KR: the semantics we propose is appropriate for a structural analysis of those conditionals that do not satisfy closure properties associated to classical logics.Source: ISTI Technical Report, ISTI-2022-TR/004, pp.1–21, 2022
Project(s): TAILOR
Casini G., Straccia U.
We introduce and investigate here a formalisation for conditionals that allows the definition of a broad class of reasoning systems. This framework covers the most popular kinds of conditional reasoning in logic-based KR: the semantics we propose is appropriate for a structural analysis of those conditionals that do not satisfy closure properties associated to classical logics.Source: ISTI Technical Report, ISTI-2022-TR/004, pp.1–21, 2022
Project(s): TAILOR
See at:
arxiv.org | ISTI Repository | CNR ExploRA
2022
Report
Open Access
A minimal deductive system for RDFS with negative statements
Straccia U., Casini G.
The triple language RDFS is designed to represent and reason with \emph{positive} statements only (e.g."antipyretics are drugs"). In this paper we show how to extend RDFS to express and reason with various forms of negative statements under the Open World Assumption (OWA). To do so, we start from rdf, a minimal, but significant RDFS fragment that covers all essential features of RDFS, and then extend it to ?rdfbotneg, allowing express also statements such as "radio therapies are non drug treatments", "Ebola has no treatment", or "opioids and antipyretics are disjoint classes". The main and, to the best of our knowledge, unique features of our proposal are: (i) rdfbotneg remains syntactically a triple language by extending rdf with new symbols with specific semantics and there is no need to revert to the reification method to represent negative triples; (ii) the logic is defined in such a way that any RDFS reasoner/store may handle the new predicates as ordinary terms if it does not want to take account of the extra capabilities; (iii) despite negated statements, every rdfbotneg knowledge base is satisfiable; (iv) the rdfbotneg entailment decision procedure is obtained from rdf via additional inference rules favouring a potential implementation; and (v) deciding entailment in rdfbotneg ranges from P to NP.Source: ISTI Technical Report, ISTI-2022-TR/005, pp.1–24, 2022
Project(s): TAILOR
Straccia U., Casini G.
The triple language RDFS is designed to represent and reason with \emph{positive} statements only (e.g."antipyretics are drugs"). In this paper we show how to extend RDFS to express and reason with various forms of negative statements under the Open World Assumption (OWA). To do so, we start from rdf, a minimal, but significant RDFS fragment that covers all essential features of RDFS, and then extend it to ?rdfbotneg, allowing express also statements such as "radio therapies are non drug treatments", "Ebola has no treatment", or "opioids and antipyretics are disjoint classes". The main and, to the best of our knowledge, unique features of our proposal are: (i) rdfbotneg remains syntactically a triple language by extending rdf with new symbols with specific semantics and there is no need to revert to the reification method to represent negative triples; (ii) the logic is defined in such a way that any RDFS reasoner/store may handle the new predicates as ordinary terms if it does not want to take account of the extra capabilities; (iii) despite negated statements, every rdfbotneg knowledge base is satisfiable; (iv) the rdfbotneg entailment decision procedure is obtained from rdf via additional inference rules favouring a potential implementation; and (v) deciding entailment in rdfbotneg ranges from P to NP.Source: ISTI Technical Report, ISTI-2022-TR/005, pp.1–24, 2022
Project(s): TAILOR
See at:
arxiv.org | ISTI Repository | CNR ExploRA
2022
Conference article
Open Access
A general framework for modelling conditional reasoning - Preliminary report
Casini G., Straccia U.
We introduce and investigate here a formalisation for conditionals that allows the definition of a broad class of reasoning systems. This framework covers the most popular kinds of conditional reasoning in logic-based KR: the semantics we propose is appropriate for a structural analysis of those conditionals that do not satisfy closure properties associated to classical logics.Source: KR 2022 - 19th International Conference on Principles of Knowledge Representation and Reasoning, pp. 112–121, Haifa, Israel, 31/07-05/08/2022
DOI: 10.24963/kr.2022/12
DOI: 10.48550/arxiv.2202.07596
Project(s): TAILOR
Metrics:
Casini G., Straccia U.
We introduce and investigate here a formalisation for conditionals that allows the definition of a broad class of reasoning systems. This framework covers the most popular kinds of conditional reasoning in logic-based KR: the semantics we propose is appropriate for a structural analysis of those conditionals that do not satisfy closure properties associated to classical logics.Source: KR 2022 - 19th International Conference on Principles of Knowledge Representation and Reasoning, pp. 112–121, Haifa, Israel, 31/07-05/08/2022
DOI: 10.24963/kr.2022/12
DOI: 10.48550/arxiv.2202.07596
Project(s): TAILOR
Metrics:
See at:
arXiv.org e-Print Archive | ISTI Repository | proceedings.kr.org | doi.org | doi.org | CNR ExploRA
2022
Conference article
Open Access
A minimal deductive system for RDFS with negative statements
Straccia U., Casini G.
The triple language RDFS is designed to represent and reason with \emph{positive} statements only (e.g."antipyretics are drugs"). In this paper we show how to extend RDFS to express and reason with various forms of negative statements under the Open World Assumption (OWA). To do so, we start from rdf, a minimal, but significant RDFS fragment that covers all essential features of RDFS, and then extend it to ?rdfbotneg, allowing express also statements such as "radio therapies are non drug treatments", "Ebola has no treatment", or "opioids and antipyretics are disjoint classes". The main and, to the best of our knowledge, unique features of our proposal are: (i) rdfbotneg remains syntactically a triple language by extending rdf with new symbols with specific semantics and there is no need to revert to the reification method to represent negative triples; (ii) the logic is defined in such a way that any RDFS reasoner/store may handle the new predicates as ordinary terms if it does not want to take account of the extra capabilities; (iii) despite negated statements, every rdfbotneg knowledge base is satisfiable; (iv) the rdfbotneg entailment decision procedure is obtained from rdf via additional inference rules favouring a potential implementation; and (v) deciding entailment in rdfbotneg ranges from P to NP.Source: KR 2022 - 19th International Conference on Principles of Knowledge Representation and Reasoning, pp. 351–361, Haifa, Israel, 31/07-05/08/2022
DOI: 10.24963/kr.2022/35
DOI: 10.48550/arxiv.2202.13750
Project(s): TAILOR
Metrics:
Straccia U., Casini G.
The triple language RDFS is designed to represent and reason with \emph{positive} statements only (e.g."antipyretics are drugs"). In this paper we show how to extend RDFS to express and reason with various forms of negative statements under the Open World Assumption (OWA). To do so, we start from rdf, a minimal, but significant RDFS fragment that covers all essential features of RDFS, and then extend it to ?rdfbotneg, allowing express also statements such as "radio therapies are non drug treatments", "Ebola has no treatment", or "opioids and antipyretics are disjoint classes". The main and, to the best of our knowledge, unique features of our proposal are: (i) rdfbotneg remains syntactically a triple language by extending rdf with new symbols with specific semantics and there is no need to revert to the reification method to represent negative triples; (ii) the logic is defined in such a way that any RDFS reasoner/store may handle the new predicates as ordinary terms if it does not want to take account of the extra capabilities; (iii) despite negated statements, every rdfbotneg knowledge base is satisfiable; (iv) the rdfbotneg entailment decision procedure is obtained from rdf via additional inference rules favouring a potential implementation; and (v) deciding entailment in rdfbotneg ranges from P to NP.Source: KR 2022 - 19th International Conference on Principles of Knowledge Representation and Reasoning, pp. 351–361, Haifa, Israel, 31/07-05/08/2022
DOI: 10.24963/kr.2022/35
DOI: 10.48550/arxiv.2202.13750
Project(s): TAILOR
Metrics:
See at:
arXiv.org e-Print Archive | ISTI Repository | proceedings.kr.org | doi.org | doi.org | CNR ExploRA
2022
Conference article
Open Access
Situated conditionals - A brief introduction
Casini G., Meyer T., Varzinczak I.
We extend the expressivity of classical conditional reasoning by introducing situation as a new parameter. The enriched conditional logic generalises the defeasible conditional setting in the style of Kraus, Lehmann, and Magidor, and allows for a refined semantics that is able to distinguish, for example, between expectations and counterfactuals. We introduce the language for the enriched logic and define an appropriate semantic framework for it. We analyse which properties generally associated with conditional reasoning are still satisfied by the new semantic framework, provide a suitable representation result, and define an entailment relation based on Lehmann and Magidor's generally-accepted notion of RationalClosure.Source: NMR 2022 - International Workshop on Non-Monotonic Reasoning 2022, pp. 151–154, Haifa, Israel, 07-09/08/2022
Project(s): TAILOR
Casini G., Meyer T., Varzinczak I.
We extend the expressivity of classical conditional reasoning by introducing situation as a new parameter. The enriched conditional logic generalises the defeasible conditional setting in the style of Kraus, Lehmann, and Magidor, and allows for a refined semantics that is able to distinguish, for example, between expectations and counterfactuals. We introduce the language for the enriched logic and define an appropriate semantic framework for it. We analyse which properties generally associated with conditional reasoning are still satisfied by the new semantic framework, provide a suitable representation result, and define an entailment relation based on Lehmann and Magidor's generally-accepted notion of RationalClosure.Source: NMR 2022 - International Workshop on Non-Monotonic Reasoning 2022, pp. 151–154, Haifa, Israel, 07-09/08/2022
Project(s): TAILOR
See at:
ceur-ws.org | ISTI Repository | CNR ExploRA
2022
Conference article
Open Access
Defeasible reasoning in RDFS
Casini G., Straccia U.
For non-monotonic logics, the notion of Rational Closure (RC) is acknowledged as one of the main approaches. In this work we present an integration of RC within the triple language RDFS (Resource Description Framework Schema), which together with OWL 2 is a major standard semantic web ontology language. To do so, we start from ?df, an RDFS fragment that covers the essential features of RDFS, and extend it to ?df?, allowing to state that two entities are incompatible/disjoint with each other. Eventually, we propose defeasible ?df? via a typical RC construction allowing to state default class/property inclusions.Source: NMR 2022 - International Workshop on Non-Monotonic Reasoning 2022, pp. 155–158, Haifa, Israel, 07-09/08/2022
Project(s): TAILOR
Casini G., Straccia U.
For non-monotonic logics, the notion of Rational Closure (RC) is acknowledged as one of the main approaches. In this work we present an integration of RC within the triple language RDFS (Resource Description Framework Schema), which together with OWL 2 is a major standard semantic web ontology language. To do so, we start from ?df, an RDFS fragment that covers the essential features of RDFS, and extend it to ?df?, allowing to state that two entities are incompatible/disjoint with each other. Eventually, we propose defeasible ?df? via a typical RC construction allowing to state default class/property inclusions.Source: NMR 2022 - International Workshop on Non-Monotonic Reasoning 2022, pp. 155–158, Haifa, Israel, 07-09/08/2022
Project(s): TAILOR
See at:
ceur-ws.org | ISTI Repository | CNR ExploRA
2022
Contribution to conference
Open Access
Proceedings of the 20th International Workshop on Non-Monotonic Reasoning (NMR 2022)
Arieli O., Casini G., Giordano L.
Proceedings of the 20th International Workshop on Non-Monotonic Reasoning (NMR2022)
Arieli O., Casini G., Giordano L.
Proceedings of the 20th International Workshop on Non-Monotonic Reasoning (NMR2022)
See at:
ceur-ws.org | ISTI Repository | CNR ExploRA
2022
Report
Open Access
InfraScience research activity report 2021
Artini M., Assante M., Atzori C., Baglioni M., Bardi A., Bove P., Candela L., Casini G., Castelli D., Cirillo R., Coro G., De Bonis M., Debole F., Dell'Amico A., Frosini L., La Bruzzo S., Lazzeri E., Lelii L., Manghi P., Mangiacrapa F., Mangione D., Mannocci A., Ottonello E., Pagano P., Panichi G., Pavone G., Piccioli T., Sinibaldi F., Straccia U.
InfraScience is a research group of the National Research Council of Italy - Institute of Information Science and Technologies (CNR - ISTI) based in Pisa, Italy. This report documents the research activity performed by this group in 2021 to highlight the major results. In particular, the InfraScience group confronted with research challenges characterising Data Infrastructures, eScience, and Intelligent Systems. The group activity is pursued by closely connecting research and development and by promoting and supporting open science. In fact, the group is leading the development of two large scale infrastructures for Open Science, i.e. D4Science and OpenAIRE. During 2021 InfraScience members contributed to the publishing of 25 papers, to the research and development activities of 18 research projects (15 funded by EU), to the organization of conferences and training events, to several working groups and task forces.Source: ISTI Annual report, 2022
DOI: 10.32079/isti-ar-2022/001
Project(s): ARIADNEplus, Blue Cloud , PerformFISH , EOSC-Pillar , DESIRA , EOSC Future , EOSCsecretariat.eu , EcoScope , RISIS 2 , OpenAIRE-Advance , OpenAIRE Nexus , SoBigData-PlusPlus
Metrics:
Artini M., Assante M., Atzori C., Baglioni M., Bardi A., Bove P., Candela L., Casini G., Castelli D., Cirillo R., Coro G., De Bonis M., Debole F., Dell'Amico A., Frosini L., La Bruzzo S., Lazzeri E., Lelii L., Manghi P., Mangiacrapa F., Mangione D., Mannocci A., Ottonello E., Pagano P., Panichi G., Pavone G., Piccioli T., Sinibaldi F., Straccia U.
InfraScience is a research group of the National Research Council of Italy - Institute of Information Science and Technologies (CNR - ISTI) based in Pisa, Italy. This report documents the research activity performed by this group in 2021 to highlight the major results. In particular, the InfraScience group confronted with research challenges characterising Data Infrastructures, eScience, and Intelligent Systems. The group activity is pursued by closely connecting research and development and by promoting and supporting open science. In fact, the group is leading the development of two large scale infrastructures for Open Science, i.e. D4Science and OpenAIRE. During 2021 InfraScience members contributed to the publishing of 25 papers, to the research and development activities of 18 research projects (15 funded by EU), to the organization of conferences and training events, to several working groups and task forces.Source: ISTI Annual report, 2022
DOI: 10.32079/isti-ar-2022/001
Project(s): ARIADNEplus
, Blue Cloud , PerformFISH , EOSC-Pillar , DESIRA , EOSC Future , EOSCsecretariat.eu , EcoScope , RISIS 2 , OpenAIRE-Advance , OpenAIRE Nexus , SoBigData-PlusPlus Metrics:
See at:
ISTI Repository | CNR ExploRA
2022
Report
Open Access
InfraScience research activity report 2022
Artini M., Assante M., Atzori C., Baglioni M., Bardi A., Bove P., Candela L., Casini G., Castelli D., Cirillo R., Coro G., De Bonis M., Debole F., Dell'Amico A., Frosini L., La Bruzzo S., Lelii L., Manghi P., Mangiacrapa F., Mangione D., Mannocci A., Ottonello E., Pagano P., Panichi G., Pavone G., Piccioli T., Sinibaldi F., Straccia U., Zoppi F.
InfraScience is a research group of the National Research Council of Italy - Institute of Information Science and Technologies (CNR - ISTI) based in Pisa, Italy. This report documents the research activity performed by this group in 2022 to highlight the major results. In particular, the InfraScience group confronted with research challenges characterising Data Infrastructures, e-Science, and Intelligent Systems. The group activity is pursued by closely connecting research and development and by promoting and supporting open science. In fact, the group is leading the development of two large scale infrastructures for Open Science, i.e. D4Science and OpenAIRE. During 2022 InfraScience members contributed to the publishing of several papers, to the research and development activities of 18 research projects (15 funded by EU), to the organization of conferences and training events, to several working groups and task forces.Source: ISTI Annual reports, 2022
DOI: 10.32079/isti-ar-2022/004
Project(s): ARIADNEplus, Blue Cloud , EOSC-Pillar , DESIRA , EOSC Future , RISIS 2 , TAILOR , SoBigData-PlusPlus
Metrics:
Artini M., Assante M., Atzori C., Baglioni M., Bardi A., Bove P., Candela L., Casini G., Castelli D., Cirillo R., Coro G., De Bonis M., Debole F., Dell'Amico A., Frosini L., La Bruzzo S., Lelii L., Manghi P., Mangiacrapa F., Mangione D., Mannocci A., Ottonello E., Pagano P., Panichi G., Pavone G., Piccioli T., Sinibaldi F., Straccia U., Zoppi F.
InfraScience is a research group of the National Research Council of Italy - Institute of Information Science and Technologies (CNR - ISTI) based in Pisa, Italy. This report documents the research activity performed by this group in 2022 to highlight the major results. In particular, the InfraScience group confronted with research challenges characterising Data Infrastructures, e-Science, and Intelligent Systems. The group activity is pursued by closely connecting research and development and by promoting and supporting open science. In fact, the group is leading the development of two large scale infrastructures for Open Science, i.e. D4Science and OpenAIRE. During 2022 InfraScience members contributed to the publishing of several papers, to the research and development activities of 18 research projects (15 funded by EU), to the organization of conferences and training events, to several working groups and task forces.Source: ISTI Annual reports, 2022
DOI: 10.32079/isti-ar-2022/004
Project(s): ARIADNEplus
, Blue Cloud , EOSC-Pillar , DESIRA , EOSC Future , RISIS 2 , TAILOR , SoBigData-PlusPlus Metrics:
See at:
ISTI Repository | CNR ExploRA
2022
Contribution to book
Open Access
Handbook of legal AI
Casini G., Robaldo L., Van Der Torre L., Villata S.
The Handbook of Legal AI presents a comprehensive overview of the state-of-the-art and trends in the research field of legal AI. The handbook provides a solid introduction to the essentials of the field for newcomers and a selection of advanced issues as a base for future research directions. As the law gets more complex, conflicting, and ever-changing, more advanced methods, most of them come from the Artifi cial Intelligence (AI) field, are required for analyzing, representing and reasoning on legal knowledge. The discipline that tackles these challenges is now known as "Legal Artificial Intelligence". Legal AI is experiencing, in particular, in the latest years growth in activity, also at the industrial level, touching a variety of issues which go from the analysis of the textual content of the law, to reasoning about legal interpretation to ethical issues of AI applications in the legal domain (e.g., the artificial judge). This Handbook presents a collection of chapters which evolves around three main topics, namely norm mining (i.e., how to automatically identify, extract, classify and interlink norms from text), reasoning about norms and regulations (i.e., how to derive new legal knowledge from the existing legal knowledge bases in such a way to address automatic legal decision making), and norm enforcement and compliance (i.e., how to check and ensure the compliance of the systems' requirements with the regulation).Source: London: College Publications Ltd, 2022
Project(s): TAILOR
Casini G., Robaldo L., Van Der Torre L., Villata S.
The Handbook of Legal AI presents a comprehensive overview of the state-of-the-art and trends in the research field of legal AI. The handbook provides a solid introduction to the essentials of the field for newcomers and a selection of advanced issues as a base for future research directions. As the law gets more complex, conflicting, and ever-changing, more advanced methods, most of them come from the Artifi cial Intelligence (AI) field, are required for analyzing, representing and reasoning on legal knowledge. The discipline that tackles these challenges is now known as "Legal Artificial Intelligence". Legal AI is experiencing, in particular, in the latest years growth in activity, also at the industrial level, touching a variety of issues which go from the analysis of the textual content of the law, to reasoning about legal interpretation to ethical issues of AI applications in the legal domain (e.g., the artificial judge). This Handbook presents a collection of chapters which evolves around three main topics, namely norm mining (i.e., how to automatically identify, extract, classify and interlink norms from text), reasoning about norms and regulations (i.e., how to derive new legal knowledge from the existing legal knowledge bases in such a way to address automatic legal decision making), and norm enforcement and compliance (i.e., how to check and ensure the compliance of the systems' requirements with the regulation).Source: London: College Publications Ltd, 2022
Project(s): TAILOR
See at:
www.collegepublications.co.uk | CNR ExploRA
2022
Journal article
Open Access
Normative change: an AGM approach
Maranhão J. S. A., Casini G., Van Der Torre L., Pigozzi G.
Studying normative change has practical and theoretical interests. Changing legal rules poses interpretation problems to determine the content of legal rules. The question of interpretation is tightly linked to those of determining the validity and the ability to produce effects of legal rules. Different formal models of normative change seem better suited to capture these dimensions: the dimension of validity appears to be better captured by the AGM approach, whereas syntactic methods are better suited to model how rules' effects are blocked or enabled. Historically, the AGM approach of belief revision (on which we focus in this chapter) was the first formal model of normative change. We provide a survey on the AGM approach along with the main criticisms made to it. We then turn to a formal analysis of normative change that combines AGM theory and input/output logic, allowing for a clear distinction between norms and obligations. Our approach addresses some of the difficulties of normative change, like the combination of constitutive and regulative rules (and the normative conflicts that may arise from such a combination), the revision and contraction of normative systems, as well as the contraction of normative systems that combine sets of constitutive and regulative rules. We end our chapter by highlighting and discussing some challenges and open problems of normative change in the AGM approach.Source: IfCoLog Journal of Logics and their Applications 9 (2022): 825–889.
Project(s): TAILOR
Maranhão J. S. A., Casini G., Van Der Torre L., Pigozzi G.
Studying normative change has practical and theoretical interests. Changing legal rules poses interpretation problems to determine the content of legal rules. The question of interpretation is tightly linked to those of determining the validity and the ability to produce effects of legal rules. Different formal models of normative change seem better suited to capture these dimensions: the dimension of validity appears to be better captured by the AGM approach, whereas syntactic methods are better suited to model how rules' effects are blocked or enabled. Historically, the AGM approach of belief revision (on which we focus in this chapter) was the first formal model of normative change. We provide a survey on the AGM approach along with the main criticisms made to it. We then turn to a formal analysis of normative change that combines AGM theory and input/output logic, allowing for a clear distinction between norms and obligations. Our approach addresses some of the difficulties of normative change, like the combination of constitutive and regulative rules (and the normative conflicts that may arise from such a combination), the revision and contraction of normative systems, as well as the contraction of normative systems that combine sets of constitutive and regulative rules. We end our chapter by highlighting and discussing some challenges and open problems of normative change in the AGM approach.Source: IfCoLog Journal of Logics and their Applications 9 (2022): 825–889.
Project(s): TAILOR
See at:
www.collegepublications.co.uk | CNR ExploRA
2022
Conference article
Closed Access
KLM-style defeasibility for restricted first-order logic
Casini G., Meyer T., Paterson-Jones G., Varzinczak I.
In this paper, we extend the KLM approach to defeasible reasoning beyond the propositional setting. We do so by making it applicable to a restricted version of first-order logic. We describe defeasibility for this logic using a set of rationality postulates, provide a suitable and intuitive semantics for it, and present a representation result characterising the semantic description of defeasibility in terms of our postulates. An advantage of our semantics is that it is sufficiently general to be applicable to other restricted versions of first-order logic as well. Based on this theoretical core, we then propose a version of defeasible entailment that is inspired by the well-known notion of Rational Closure as it is defined for defeasible propositional logic and defeasible description logics. We show that this form of defeasible entailment is rational in the sense that it adheres to the full set of rationality postulates.Source: RuleML+RR 2022 - International Joint Conference on Rules and Reasoning, pp. 81–94, Berlin, Germany, 26-28/09/2022
DOI: 10.1007/978-3-031-21541-4_6
Project(s): TAILOR
Metrics:
Casini G., Meyer T., Paterson-Jones G., Varzinczak I.
In this paper, we extend the KLM approach to defeasible reasoning beyond the propositional setting. We do so by making it applicable to a restricted version of first-order logic. We describe defeasibility for this logic using a set of rationality postulates, provide a suitable and intuitive semantics for it, and present a representation result characterising the semantic description of defeasibility in terms of our postulates. An advantage of our semantics is that it is sufficiently general to be applicable to other restricted versions of first-order logic as well. Based on this theoretical core, we then propose a version of defeasible entailment that is inspired by the well-known notion of Rational Closure as it is defined for defeasible propositional logic and defeasible description logics. We show that this form of defeasible entailment is rational in the sense that it adheres to the full set of rationality postulates.Source: RuleML+RR 2022 - International Joint Conference on Rules and Reasoning, pp. 81–94, Berlin, Germany, 26-28/09/2022
DOI: 10.1007/978-3-031-21541-4_6
Project(s): TAILOR
Metrics:
See at:
doi.org | link.springer.com | CNR ExploRA
2021
Conference article
Open Access
Contextual conditional reasoning
Casini G., Meyer T., Varzinczak I.
We extend the expressivity of classical conditional reasoning by introducing context as a new parameter. The enriched conditional logic generalises the defeasible conditional setting in the style of Kraus, Lehmann, and Magidor, and allows for a refined semantics that is able to distinguish, for example, between expectations and counterfactuals. In this paper we introduce the language for the enriched logic and define an appropriate semantic framework for it. We analyse which properties generally associated with conditional reasoning are still satisfied by the new semantic framework, provide a suitable representation result, and define an entailment relation based on Lehmann and Magidor's generally-accepted notion of Rational Closure.Source: AAAI-21 - The Thirty-Fifth AAAI Conference on Artificial Intelligence, pp. 6254–6261, Online Conference, 2-9/2/2021
Casini G., Meyer T., Varzinczak I.
We extend the expressivity of classical conditional reasoning by introducing context as a new parameter. The enriched conditional logic generalises the defeasible conditional setting in the style of Kraus, Lehmann, and Magidor, and allows for a refined semantics that is able to distinguish, for example, between expectations and counterfactuals. In this paper we introduce the language for the enriched logic and define an appropriate semantic framework for it. We analyse which properties generally associated with conditional reasoning are still satisfied by the new semantic framework, provide a suitable representation result, and define an entailment relation based on Lehmann and Magidor's generally-accepted notion of Rational Closure.Source: AAAI-21 - The Thirty-Fifth AAAI Conference on Artificial Intelligence, pp. 6254–6261, Online Conference, 2-9/2/2021
See at:
ojs.aaai.org | ISTI Repository | CNR ExploRA
2021
Report
Open Access
Situated conditional reasoning
Casini G., Meyer T., Varzinczak I.
Conditionals are useful for modelling, but aren't always sufficiently expressive for capturing information accurately. In this paper we make the case for a form of conditional that is situation-based. These conditionals are more expressive than classical conditionals, are general enough to be used in several application domains, and are able to distinguish, for example, between expectations and counterfactuals. Formally, they are shown to generalise the conditional setting in the style of Kraus, Lehmann, and Magidor. We show that situation-based conditionals can be described in terms of a set of rationality postulates. We then propose an intuitive semantics for these conditionals, and present a representation result which shows that our semantic construction corresponds exactly to the description in terms of postulates. With the semantics in place, we proceed to define a form of entailment for situated conditional knowledge bases, which we refer to as minimal closure. It is reminiscent of and, indeed, inspired by, the version of entailment for propositional conditional knowledge bases known as rational closure. Finally, we proceed to show that it is possible to reduce the computation of minimal closure to a series of propositional entailment and satisfiability checks. While this is also the case for rational closure, it is somewhat surprising that the result carries over to minimal closure.Source: ISTI Technical Report, ISTI-2021-TR/009, 2021
DOI: 10.32079/isti-tr-2021/009
Metrics:
Casini G., Meyer T., Varzinczak I.
Conditionals are useful for modelling, but aren't always sufficiently expressive for capturing information accurately. In this paper we make the case for a form of conditional that is situation-based. These conditionals are more expressive than classical conditionals, are general enough to be used in several application domains, and are able to distinguish, for example, between expectations and counterfactuals. Formally, they are shown to generalise the conditional setting in the style of Kraus, Lehmann, and Magidor. We show that situation-based conditionals can be described in terms of a set of rationality postulates. We then propose an intuitive semantics for these conditionals, and present a representation result which shows that our semantic construction corresponds exactly to the description in terms of postulates. With the semantics in place, we proceed to define a form of entailment for situated conditional knowledge bases, which we refer to as minimal closure. It is reminiscent of and, indeed, inspired by, the version of entailment for propositional conditional knowledge bases known as rational closure. Finally, we proceed to show that it is possible to reduce the computation of minimal closure to a series of propositional entailment and satisfiability checks. While this is also the case for rational closure, it is somewhat surprising that the result carries over to minimal closure.Source: ISTI Technical Report, ISTI-2021-TR/009, 2021
DOI: 10.32079/isti-tr-2021/009
Metrics:
See at:
ISTI Repository | CNR ExploRA