We study strategy improvement algorithms for mean-payoff and parity games. We describe a structural property of these games, and we show that these structures can affect the behaviour of strategy improvement. We show ...
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ISBN:
(纸本)9783642175107
We study strategy improvement algorithms for mean-payoff and parity games. We describe a structural property of these games, and we show that these structures can affect the behaviour of strategy improvement. We show how awareness of these structures can be used to accelerate strategy improvement algorithms. We call our algorithms non-oblivious because they remember properties of the game that they have discovered in previous iterations. We show that non-oblivious strategy improvement algorithms perform well on examples that are known to be hard for oblivious strategy improvement. Hence, we argue that previous strategy improvement algorithms fail because they ignore the structural properties of the game that they are solving.
the objective of control generation in logicprogramming is to automatically derive a computation rule for a program that is efficient and yet does not compromise program correctness. Progress in solving this importan...
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the tool cc Τ is an implementation for testing various parameterised notions of program correspondence between logic programs under the answer-set semantics, based on reductions to quantified propositional logic. One...
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Recently, there has been an increase of reported security threats hitting organizations. Some of them are originated from the assignments to users of inappropriate permissions on organizational sensitive data. thus it...
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ISBN:
(纸本)9780769545356
Recently, there has been an increase of reported security threats hitting organizations. Some of them are originated from the assignments to users of inappropriate permissions on organizational sensitive data. thus it is crucial for organizations to recognize as early as possible the risks deriving by inappropriate access right management and to identify the solutions that they need to prevent such risks. In this paper, we propose a framework to identify threats during the requirements analysis of organizations' IT systems. With respect to other works which have attempted to include security analysis into requirement engineering process (e.g., KAOS, Elahi et al., Asnar et al.), our framework does not rely on the level of expertise of the security analyst to detect threats but allows to automatically identify threats that derive from inappropriate access management. To capture the organization's setting and the system stakeholders' requirements, we adopt SI* [1], a requirement engineering framework founded on the concepts of actors, goals, tasks and resources. this framework extends SI* with a reasoning technique that identifies potential security threats on resources and relevant goals. the reasoning is based on Answer Set programming ( ASP) logic rules that take into account the relationships between resources and the delegation of permission relations between actors. We illustrate this framework using an eHealth scenario.
We describe an abstract proof-theoretic framework based on normal-form proofs, defined using well-founded orderings on proof objects. this leads to robust notions of canonical presentation and redundancy. Fairness of ...
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ISBN:
(纸本)9783540710691
We describe an abstract proof-theoretic framework based on normal-form proofs, defined using well-founded orderings on proof objects. this leads to robust notions of canonical presentation and redundancy. Fairness of deductive mechanisms - in this general framework - leads to completeness or saturation. the method has so far been applied to the equational, Horn-clause, and deduction-modulo cases.
In this paper, we devise a general framework for formalizing Description logic Based Dynamic Systems that is parametric w.r.t. the description logic knowledge base and the progression mechanism of interest. Using this...
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Expert knowledge can often be represented using default rules of the form "if A then typically B". In a probabilistic framework, such default rules can be seen as constraints on what should be derivable by M...
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ISBN:
(数字)9783319405667
ISBN:
(纸本)9783319405667;9783319405650
Expert knowledge can often be represented using default rules of the form "if A then typically B". In a probabilistic framework, such default rules can be seen as constraints on what should be derivable by MAP-inference. We exploit this idea for constructing a Markov logic network M from a set of first-order default rules D, such that MAP inference from M exactly corresponds to default reasoning from D, where we view first-order default rules as templates for the construction of propositional default rules. In particular, to construct appropriate Markov logic networks, we lift three standard methods for default reasoning. the resulting Markov logic networks could then be refined based on available training data. Our method thus offers a convenient way of using expert knowledge for constraining or guiding the process of learning Markov logic networks.
In information security, representation and reasoning of authorization policy has been a key research topic in this field especially in a sophisticated information sharing and exchange environment [6, 7, 9]. In such a...
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ISBN:
(纸本)9781943436040
In information security, representation and reasoning of authorization policy has been a key research topic in this field especially in a sophisticated information sharing and exchange environment [6, 7, 9]. In such a scenario, an user's request to access the system may not be able to decide straightaway, it may initiate a sequence of complex executions of authorization commands in order to determine either to grant or deny such a request. Becker and Nanz's logic of State-Modifying Policies (SMP) is a formal system addressing such problem in access control. In this paper, we provide a declarative semantics for SMP through a translation from SMP to Answer Set programming (ASP) and propose a system prototype to implement our approach. Our experimental results show that our ASP implementation for SMP reasoning is effective to deal with real world problem domains. Copyright ISCA, CAINE 2016.
We present a framework for a declarative approach to spatio-temporal reasoning on geographical data, based on the constraint logical language STACLP, which offers deductive and inductive capabilities. It can be exploi...
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ISBN:
(纸本)3540255605
We present a framework for a declarative approach to spatio-temporal reasoning on geographical data, based on the constraint logical language STACLP, which offers deductive and inductive capabilities. It can be exploited for a deductive rule-based approach to represent domain knowledge on data. Furthermore, it is well suited to model trajectories of moving objects, which can be analysed by using inductive techniques, like clustering, in order to find common movement patterns. A sketch of a case study on behavioural ecology is presented.
In this PhD project, we present an approach to the problem of determinacy inference in logic programs with cut, which treats cut uniformly and contextually. the overall aim is to develop a theoretical analysis, abstra...
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ISBN:
(纸本)9783939897316
In this PhD project, we present an approach to the problem of determinacy inference in logic programs with cut, which treats cut uniformly and contextually. the overall aim is to develop a theoretical analysis, abstract it to a suitable domain and prove boththe concrete analysis and the abstraction correct in a formal theorem prover (Coq). A crucial advantage of this approach, besides the guarantee of correctness, is the possibility of automatically extracting an implementation of the analysis.
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