Przymusinski's Autoepistemic logic of Knowledge and Belief (AELKB) is a unifying framework for various non-monotonic formalisms. In this paper we present a semantic characterization of AELKB in terms of Dynamic Kr...
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ISBN:
(纸本)3540667490
Przymusinski's Autoepistemic logic of Knowledge and Belief (AELKB) is a unifying framework for various non-monotonic formalisms. In this paper we present a semantic characterization of AELKB in terms of Dynamic Kripke Structures (DKS). A DKS is composed of two components - a static one (a Kripke structure) and a dynamic one (a set of transformations). Transformations between possible worlds correspond to hypotheses generation and to revisions. therefore they enable to define a semantics of insertions to and revisions of AELKB-theories. A computation of the transformations (between possible worlds) is based on (an enhanced) model-checking. the transformations may be used as a method of computing static autoepistemic expansions.
Association rules are often utilized in web recommendation systems for creation of suggested items lists. However, lists obtained in this way may be too short. Indirect association rules are introduced to extend class...
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ISBN:
(纸本)0769522866
Association rules are often utilized in web recommendation systems for creation of suggested items lists. However, lists obtained in this way may be too short. Indirect association rules are introduced to extend classical, direct association rules and supplement the knowledge they contribute. the relation between ranking lists created on the basis of association rules and hyperlinks existing, on web pages has also been examined in the paper.
there are two ways to calculate synaptic weights for neurons in logicprogramming. there are by using Hebbian learning or by Wan Abdullah's method Hebbian learning for governing events corresponding to some respec...
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ISBN:
(纸本)9780769533599
there are two ways to calculate synaptic weights for neurons in logicprogramming. there are by using Hebbian learning or by Wan Abdullah's method Hebbian learning for governing events corresponding to some respective program clauses is equivalent with learning using Wan Abdullah's method for the same respective program clauses. We will evaluate experimentally the logical equivalent between these two types of learning (Wan Abdullah's method and Hebbian learning)for the same respective clauses (same underlying logical rules) in this paper. the computer simulation that had been carried out support this theory.
Relational algebras as developed by Codd and his followers are extended by noting an equivalence with functional languages. this leads to higher order relations, recursive definitions of relations, and the use of high...
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this paper illustrates the use of Inductive logicprogramming to program agents that learn rules of behaviour from simulated histories of their embedding systems. We have shown how a ILP system can be used to learn ru...
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ISBN:
(纸本)0889865248
this paper illustrates the use of Inductive logicprogramming to program agents that learn rules of behaviour from simulated histories of their embedding systems. We have shown how a ILP system can be used to learn rules in a representation very close to the one used to guide the simulation of a multi-agent system. this establishes the feasibility of embedding (resource- bounded) learners as agents that take part in simulating a complex system.
In this paper, we shall provide a translation of a class of causal theories in (Lin [3]) to Gelfond and Lifschitz's disjunctive logic programs with classical negation [1]. We found this translation interesting for...
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ISBN:
(纸本)3540667490
In this paper, we shall provide a translation of a class of causal theories in (Lin [3]) to Gelfond and Lifschitz's disjunctive logic programs with classical negation [1]. We found this translation interesting for at least the following two reasons: it provides a basis on which a wide class of causal theories in ([3]) can be computed;and it sheds some new lights on the nature of the causal theories in [3]. Our translation is in many ways similar to the one given in [9,2]. Our main result is a theorem that shows how action precondition and fully instantiated successor state axioms can be computed from the answer sets of the translated logic program.
In this paper we present an Action Language-Answer Set programming based approach to solving planning and scheduling problems in hybrid domains - domains that exhibit both discrete and continuous behavior. We use acti...
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Model transformation is defined as a central concept in model driven engineering. Identifying the transformation rules is nontrivial task, where it might be much easier for the experts to provide examples of the trans...
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ISBN:
(纸本)9781479932795
Model transformation is defined as a central concept in model driven engineering. Identifying the transformation rules is nontrivial task, where it might be much easier for the experts to provide examples of the transformations rather than specifying complete and consistent rules. the examples provided by expert represent their knowledge in the domain. thus, it is much beneficial to utilize a set of examples, i.e. pairs of transformation source and target models, in order to learn transformation rules. Machine learning (ML) techniques proved their ability of learning relations and concepts in various domains. In this paper, we aim to apply Inductive logicprogramming (ILP) for learning the transformation rules between the requirements analysis and software design based on a set of pairs of transformation analysis and design models. ALEPH and GILPS systems have been employed, individually, to induce the intended transformation rules;however the resultant rules don't accommodate the desire transformations. thus, in this paper we focus on identifying the problem of analysis-design transformation and discussing the derived rules as well as the limitations of the current ILP systems.
Smart Contract (SC) programming Languages (PL) are inspired by Non-SC PLs. Many, like Solidity, use an object-oriented approach with interfaces and inheritance-based subtyping. However, the main focus of these concept...
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ISBN:
(纸本)9798350317824
Smart Contract (SC) programming Languages (PL) are inspired by Non-SC PLs. Many, like Solidity, use an object-oriented approach with interfaces and inheritance-based subtyping. However, the main focus of these concepts is on abstraction and extend-ability, whereas for SC Systems, robust, secure and composable SCs are of higher importance. Further, despite supporting inheritance, Solidity and other SC PLs fail to leverage the full benefits of the object-oriented paradigm when multiple SCs are involved. this work presents an approach to SC composability that enables highly composable and secure SCs by encapsulating logic in small traits that serve as interfaces.
We study the fixed-parameter complexity of various problems in Al and nonmonotonic reasoning. We show that a number of relevant parameterized problems in these areas are fixed-parameter tractable. Among these problems...
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ISBN:
(纸本)3540667490
We study the fixed-parameter complexity of various problems in Al and nonmonotonic reasoning. We show that a number of relevant parameterized problems in these areas are fixed-parameter tractable. Among these problems are constraint satisfaction problems with bounded treewidth and fixed domain, restricted satisfiability problems, propositional logicprogramming under the stable model semantics where the parameter is the dimension of a feedback vertex set of the program's dependency graph, and circumscriptive inference from a positive k-CNF restricted to models of bounded size. We also show that circumscriptive inference from a general propositional theory, when the attention is restricted to models of bounded size, is fixed-parameter intractable and is actually complete for a novel fixed-parameter complexity class.
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