the tendency to accept or reject arguments based on own beliefs or prior knowledge rather than on the reasoning process is called the belief-bias effect. A psychological syllogistic reasoning task shows this phenomeno...
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the tendency to accept or reject arguments based on own beliefs or prior knowledge rather than on the reasoning process is called the belief-bias effect. A psychological syllogistic reasoning task shows this phenomenon, wherein participants were asked whether they accept or reject a given syllogism. We discuss one case which is commonly assumed to be believable but not logically valid. By introducing abnormalities, abduction and background knowledge, we model this case under the weak completion semantics. Our formalization reveals new questions about observations and their explanations which might include some relevant prior abductive contextual information concerning some side-effect. Inspection points, introduced by Pereira and Pinto, allow us to express these definitions syntactically and intertwine them into an operational semantics.
the proceedings contain 85 papers. the topics discussed include: logic programs with ordered disjunction: first-order semantics and expressiveness;constructive negation in extensional higher-order logicprogramming;th...
the proceedings contain 85 papers. the topics discussed include: logic programs with ordered disjunction: first-order semantics and expressiveness;constructive negation in extensional higher-order logicprogramming;the well-founded semantics is the principle of inductive definition, revisited;the semantics of gringo and infinitary propositional formulas;an SCC recursive meta-algorithm for computing preferred labelings in abstract argumentation;on the revision of argumentation systems: minimal change of arguments statuses;a dynamic logic framework for abstract argumentation;analyzing the computational complexity of abstract dialectical frameworks via approximation fixpoint theory;skolemization for weighted first-order model counting;and belief change operations: a short history of nearly everything, told in dynamic logic of propositional assignments.
We investigate conjunctive query inseparability of description logic (DL) knowledge bases (KBs) with respect to a given signature, a fundamental problem for KB versioning, module extraction, forgetting and knowledge e...
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We investigate conjunctive query inseparability of description logic (DL) knowledge bases (KBs) with respect to a given signature, a fundamental problem for KB versioning, module extraction, forgetting and knowledge exchange. We study the data and combined complexity of deciding KB query inseparability for fragments of Horn-ALCHI, including the DLs underpinning OWL 2 QL and OWL 2EL. While all of these DLs are P-complete for data complexity, the combined complexity ranges from P to EXPTIME and 2EXPTIME. We also resolve two major open problems for OWL 2 QL by showing that TBox query inseparability and the membership problem for universal UCQ-solutions in knowledge exchange are both EXPTIME-complete for combined complexity.
Codatatypes are absent from many programming and specification languages. We make a case for their importance by revisiting a classical result: the completeness theorem for first-order logic established through a Gent...
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ISBN:
(纸本)9783319085876;9783319085869
Codatatypes are absent from many programming and specification languages. We make a case for their importance by revisiting a classical result: the completeness theorem for first-order logic established through a Gentzen system. the core of the proof establishes an abstract property of possibly infinite derivation trees, independently of the concrete syntax or inference rules. this separation of concerns simplifies the presentation. the abstract proof can be instantiated for a wide range of Gentzen and tableau systems as well as various flavors of first-order logic. the corresponding Isabelle/HOL formalization demonstrates the recently introduced support for codatatypes and the Haskell code generator.
Today's propositional satisfiability (SAT) solvers are extremely powerful and can be used as an efficient back-end for solving NP-complete problems. However, many fundamental problems in knowledge representation a...
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Today's propositional satisfiability (SAT) solvers are extremely powerful and can be used as an efficient back-end for solving NP-complete problems. However, many fundamental problems in knowledge representation and reasoning are located at the second level of the Polynomial Hierarchy or even higher, and hence polynomial-time transformations to SAT are not possible, unless the hierarchy collapses. Recent research shows that in certain cases one can break through these complexity barriers by fixed-parameter tractable (fpt) reductions which exploit structural aspects of problem instances in terms of problem parameters. In this paper we develop a general theoretical framework that supports the classification of parameterized problems on whether they admit such an fpt-reduction to SAT or not. We instantiate our theory by classifying the complexities of several case study problems, with respect to various natural parameters. these case studies include the consistency problem for disjunctive answer set programming and a robust version of constraint satisfaction.
We investigate the potential of logicprogramming (LP) to model morality aspects studied in philosophy and psychology. We do so by identifying three morality aspects that appear in our view amenable to computational m...
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this book constitutes the refereed proceedings of the 12thinternationalconference on artificialintelligence and Symbolic Computation, AISC 2014, held in Seville, Spain, in December 2014. the 15 full papers presente...
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ISBN:
(数字)9783319137704
ISBN:
(纸本)9783319137698;9783319137704
this book constitutes the refereed proceedings of the 12thinternationalconference on artificialintelligence and Symbolic Computation, AISC 2014, held in Seville, Spain, in December 2014. the 15 full papers presented together with 2 invited papers were carefully reviewed and selected from 22 submissions. the goals were on one side to bind mathematical domains such as algebraic topology or algebraic geometry to AI but also to link AI to domains outside pure algorithmic computing. the papers address all current aspects in the area of symbolic computing and AI: basic concepts of computability and new Turing machines; logics including non-classical ones; reasoning; learning; decision support systems; and machine intelligence and epistemology and philosophy of symbolic mathematical computing.
We propose a representation method for semantically enriched business processes by combining in a uniform logical framework boththe procedural and the domain dependent knowledge. First, we define a rule-based procedu...
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ISBN:
(纸本)9783662444405;9783662444399
We propose a representation method for semantically enriched business processes by combining in a uniform logical framework boththe procedural and the domain dependent knowledge. First, we define a rule-based procedural semantics for a relevant fragment of BPMN, a very popular graphical notation for specifying business processes. Our semantics defines a state transition system by following an approach similar to the Fluent Calculus, and allows us to specify state change in terms of preconditions and effects of the enactment of activities. then, we show how the procedural process knowledge can be seamlessly integrated withthe domain knowledge specified by using the OWL-RL rule-based ontology language. As a result, our framework provides a wide range of reasoning services by using standard logicprogramming inference engines.
Angry Birds is a popular video game where the task is to kill pigs protected by a structure composed of different building blocks that observe the laws of physics. the structure can be destroyed by shooting the angry ...
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Angry Birds is a popular video game where the task is to kill pigs protected by a structure composed of different building blocks that observe the laws of physics. the structure can be destroyed by shooting the angry birds at it. the fewer birds we use and the more blocks we destroy, the higher the score. One approach to solve the game is by analysing the structure and identifying its strength and weaknesses. this can then be used to decide where to hit the structure withthe birds. In this paper we use a qualitative spatial reasoning approach for this task. We develop a novel qualitative spatial calculus for representing and analysing the structure. Our calculus allows us to express and evaluate structural properties and rules, and to infer for each building block which of these properties and rules are satisfied. We use this to compute a heuristic value for each block that corresponds to how useful it is to hit that block. We evaluate our approach by comparing the suggested shot with other possible shots.
logic and probability theory are two of the most important branches of mathematics and each has played a significant role in artificialintelligence (AI) research. Beginning with Leibniz, scholars have attempted to un...
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ISBN:
(纸本)9783319087955;9783319087948
logic and probability theory are two of the most important branches of mathematics and each has played a significant role in artificialintelligence (AI) research. Beginning with Leibniz, scholars have attempted to unify logic and probability. For "classical" AI, based largely on first-order logic, the purpose of such a unification is to handle uncertainty and facilitate learning from real data;for "modern" AI, based largely on probability theory, the purpose is to acquire formal languages with sufficient expressive power to handle complex domains and incorporate prior knowledge. this paper provides a brief summary of an invited talk describing efforts in these directions, focusing in particular on open-universe probability models that allow for uncertainty about the existence and identity of objects.
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