| 1. |
- Doherty, Patrick, et al.
(författare)
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Rough Forgetting
- 2020
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Ingår i: Rough Sets. IJCRS 2020. - Cham : Springer. - 9783030527051 - 9783030527044 ; , s. 3-18
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Konferensbidrag (refereegranskat)abstract
- Recent work in the area of Knowledge Representation and Reasoning has focused on modification and optimization of knowledge bases (KB) through the use of forgetting operators of the form forget(KB, (R) over bar), where (R) over bar is a set of relations in the language signature used to specify the KB. The result of this operation is a new KB where the relations in (R) over bar are removed from the KB in a principled manner resulting in a more efficient representation of the KB for different purposes. The forgetting operator is also reflected semantically in terms of the relation between the original models of the KB and the models for the revised KB after forgetting. In this paper, we first develop a rough reasoning framework where our KBs consist of rough formulas with a semantics based on a generalization of Kleene algebras. Using intuitions from the classical case, we then define a forgetting operator that can be applied to rough KBs removing rough relations. A constructive basis for generating a new KB as the result of applying the forgetting operator to a rough KB is specified using second-order quantifier elimination techniques. We show the application of this technique with some practical examples.
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| 2. |
- Doherty, Patrick, 1957-, et al.
(författare)
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Rough set reasoning using answer set programs
- 2021
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Ingår i: International Journal of Approximate Reasoning. - : Elsevier. - 0888-613X .- 1873-4731. ; 130:March, s. 126-149
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Tidskriftsartikel (refereegranskat)abstract
- Reasoning about uncertainty is one of the main cornerstones of Knowledge Representation. Formal representations of uncertainty are numerous and highly varied due to different types of uncertainty intended to be modeled such as vagueness, imprecision and incompleteness. There is a rich body of theoretical results that has been generated for many of these approaches. It is often the case though, that pragmatic tools for reasoning with uncertainty lag behind this rich body of theoretical results. Rough set theory is one such approach for modeling incompleteness and imprecision based on indiscernibility and its generalizations. In this paper, we provide a pragmatic tool for constructively reasoning with generalized rough set approximations that is based on the use of Answer Set Programming (Asp). We provide an interpretation of answer sets as (generalized) approximations of crisp sets (when possible) and show how to use Asp solvers as a tool for reasoning about (generalized) rough set approximations situated in realistic knowledge bases. The paper includes generic Asp templates for doing this and also provides a case study showing how these techniques can be used to generate reducts for incomplete information systems. Complete, ready to run clingo Asp code is provided in the Appendix, for all programs considered. These can be executed for validation purposes in the clingo Asp solver.
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| 3. |
- Dunin-Keplicz, Barbara, et al.
(författare)
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A Framework for Organization-Centered Doxastic Reasoning
- 2020
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Ingår i: 24th International Conference on Knowledge-Based and Intelligent Information & Engineering Systems. - : Elsevier. ; , s. 3019-3028
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Konferensbidrag (refereegranskat)
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| 4. |
- Dunin-Keplicz, Barbara, et al.
(författare)
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Modeling and Shadowing Paraconsistent BDI Agents
- 2022
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Ingår i: 10th International Workshop on Engineering Multi-Agent Systems.
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- For over three decades researchers have been studying the BDI modelof agency. Many robust multiagent systems have been developed, and a numberof BDI logics have been studied. Following this intensive development phase, theimportance of integrating BDI models with inconsistency handling and revisiontheory have been emphasized. There is also a demand for a tighter connectionbetween BDI-based implementations and BDI logics. In this paper, we addressthese postulates by introducing a novel, paraconsistent logical BDI model close toimplementation, with building blocks that can be represented as SQL/rule-baseddatabases. Importantly, tractability is achieved by reasoning as querying. Thisstands in a sharp contrast to the high complexity of BDI logics. We also extendbelief shadowing, a shallow and lightweight alternative to deep and computation-ally demanding belief revision, to encompass agents’ motivational attitudes.
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| 5. |
- Dunin-Keplicz, Barbara, et al.
(författare)
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Shadowing in Many-Valued Nested Structures
- 2020
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Ingår i: 2020 IEEE 50th International Symposium on Multiple-Valued Logic (ISMVL). - : IEEE. - 9781728154077 - 9781728154060 - 9781728154053 ; , s. 230-236
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Konferensbidrag (refereegranskat)abstract
- Belief shadowing is a relatively recent approach to belief change. In essence, shadowing depends on accepting beliefs of others at the expense of dismissing, perhaps temporarily, some of the own ones. As a transient belief change, it is useful when an agent, acting as a group member or playing a particular role, has to adopt adequate "external" beliefs. So far two forms of shadowing, single and multiple, have been considered. While the former specifies shadowing when an agent belongs to a single group or plays a single role, multiple shadowing relaxes this restriction.In the paper we generalize shadowing to arbitrary finitely many-valued logics and consider more complex semantical structures allowing arbitrarily nested sets of worlds. We show that in this general setting multiple shadowing can be represented by single shadowing. The complexity of queries involving such generic shadowing operators is also analyzed.
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| 6. |
- Linh Anh, Nguyen, et al.
(författare)
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Optimization Models for Medical Procedures Relocation
- 2021
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Ingår i: 25th KES International Conference on Knowledge-Based and Intelligent Information & Engineering Systems (KES). - : Elsevier. ; , s. 2058-2067
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Konferensbidrag (refereegranskat)abstract
- As a side-effect of the Covid-19 pandemic, significant decreases in medical procedures for noncommunicable diseases have been observed. This calls for a decision support assisting in the analysis of opportunities to relocate procedures among hospitals in an efficient or, preferably, optimal manner. In the current paper we formulate corresponding decision problems and develop linear (mixed integer) programming models for them. Since solving mixed integer programming problems is NP-complete, we verify experimentally their usefulness using real-world data about urological procedures. We show that even for large models, with millions of variables, the problems’ instances are solved in perfectly acceptable time.
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| 7. |
- Szalas, Andrzej, Professor, 1956-
(författare)
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A Paraconsistent ASP-like Language with Tractable Model Generation
- 2020
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Ingår i: Journal of Applied Logics - IfCoLog Journal of Logic and Applications. - London : College Publications. - 2631-9810 .- 2631-9829. ; 7:3, s. 361-389
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Tidskriftsartikel (refereegranskat)abstract
- Answer Set Programming (ASP) is nowadays a dominant rule-based knowledge representation tool. Though existing ASP variants enjoy efficient implementations, generating an answer set remains intractable. The goal of this research is to define a new ASP-like rule language, 4SP, with tractable model generation. The language combines ideas of ASP and a paraconsistent rule language 4QL. Though 4SP shares the syntax of ASP and for each program all its answer sets are among 4SP models, the new language differs from ASP in its logical foundations, the intended methodology of its use and complexity of computing models. As we show in the paper, 4QL can be seen as a paraconsistent counterpart of ASP programs stratified with respect to default negation. Although model generation for 4QL programs is tractable, dropping stratification makes it intractable for both 4QL and ASP. To retain tractability while allowing non-stratified programs, in 4SP we introduce trial expressions interlacing programs with hypotheses as to the truth values of default negations. This allows us to develop a model generation algorithm with deterministic polynomial time complexity. We also show relationships among 4SP, ASP and 4QL.
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| 8. |
- Szalas, Andrzej, Professor, 1956-
(författare)
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Inheriting and Fusing Beliefs of Logically Heterogeneous Objects
- 2022
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Ingår i: 26th International Conference on Knowledge-Based and Intelligent Information & Engineering Systems. - : Elsevier. ; , s. 299-308
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Konferensbidrag (refereegranskat)abstract
- Inheritance has intensively been studied in both object-oriented programming (Oop) and knowledge representation and reasoning (KRR). On the other hand, the approaches to multiple inheritance and related method resolution, developed in both domains, remain separated. The primary goal of this paper is to demonstrate how these approaches may be integrated using inheritance expressions. In particular, we examine inheritance as a belief bases management machinery designed to operate in dynamically changing environments where objects are embedded and act. We focus on objects that are belief bases containers, potentially participating in complex distributed reasoning scenarios. We show that inheritance expressions, inspired both by Oop and KRR, provide a simple yet flexible and powerful means for expressing inheritance and related belief/knowledge fusion.
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| 9. |
- Szalas, Andrzej, Professor, 1956-
(författare)
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Many-Valued Dynamic Object-Oriented Inheritance and Approximations
- 2021
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Ingår i: International Joint Conference on Rough Sets. - Cham : Springer. - 9783030873332 - 9783030873349 ; , s. 103-119
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Konferensbidrag (refereegranskat)abstract
- The majority of contemporary software systems are developed using object-oriented tools and methodologies, where constructs like classes, inheritance and objects are first-class citizens. In the current paper we provide a novel formal framework for many-valued object-oriented inheritance in rule-based query languages. We also relate the framework to rough set-like approximate reasoning. Rough sets and their generalizations have intensively been studied and applied. However, the mainstream of the area mainly focuses on the context of information and decision tables. Therefore, approximations defined in the much richer object-oriented contexts generalize known approaches.
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| 10. |
- Szalas, Andrzej, Professor, 1956-
(författare)
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On the Probability and Cost of Ignorance, Inconsistency, Nonsense and More
- 2020
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Ingår i: Journal of Multiple-Valued Logic and Soft Computing. - Philadelphia, USA : Old City Publishing. - 1542-3980 .- 1542-3999. ; 34:5-6, s. 423-450
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Tidskriftsartikel (refereegranskat)abstract
- Ignorance, inconsistency, nonsense and similar phenomena are omnipresent in everyday reasoning. They have been intensively studied, especially in the area of multiple-valued logics. Therefore we develop a framework for belief bases, combining multiple-valued and probabilistic reasoning, with the main focus on the way belief bases are actually used and accessed through queries.As an implementation tool we use a probabilistic programming language PROBLOG. Though based on distribution semantics with the independence assumption, we show how its constructs can successfully be used in implementing the considered logics and belief bases. In particular, we develop a technique for shifting probabilistic dependencies to the level of symbolic parts of belief bases.We also discuss applications of the framework in reasoning with Likert-type scales, widely exploited in questionnaire-based experimental research in psychology, economics, sociology, politics, public opinion measurements, and related areas.
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