We endow Brewka's prioritised default logic (PDL) with argumentation semantics using the ASPIC(+) framework for structured argumentation. We prove that the conclusions of the justified arguments correspond to the ...
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ISBN:
(纸本)9781450342391
We endow Brewka's prioritised default logic (PDL) with argumentation semantics using the ASPIC(+) framework for structured argumentation. We prove that the conclusions of the justified arguments correspond to the prioritised default extensions in a normatively rational manner. Argumentation semantics for PDL will allow for the application of argument game proof theories to the process of inference in PDL, making the reasons for accepting a conclusion transparent and the inference process more intuitive. this also opens up the possibility for argumentation-based distributed reasoning and communication amongst agents with PDL representations of mental attitudes.
the paper presents a new logic for reasoning about the formation of beliefs through perception or through inference in non-omniscient resource-bounded agents. the logic distinguishes the concept of explicit belief fro...
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ISBN:
(纸本)9781450342391
the paper presents a new logic for reasoning about the formation of beliefs through perception or through inference in non-omniscient resource-bounded agents. the logic distinguishes the concept of explicit belief from the concept of background knowledge. this distinction is reflected in its formal semantics and axiomatics: (i) we use a non-standard semantics putting together a neighbourhood semantics for explicit beliefs and relational semantics for background knowledge, and (ii) we have specific axioms in the logic highlighting the relationship between the two concepts. Mental operations of perceptive type and inferential type, having effects on epistemic states of agents, are primitives in the object language of the logic. At the semantic level, they are modelled as special kinds of model-update operations, in the style of dynamic epistemic logic (DEL). Results about axiomatization, decidability and complexity for the logic are given in the paper.
Horn formulae are widely used in different settings that include logicprogramming, answer set programming, description logics, deductive databases, and system verification, among many others. One concrete example is ...
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ISBN:
(数字)9783319487588
ISBN:
(纸本)9783319487588;9783319487571
Horn formulae are widely used in different settings that include logicprogramming, answer set programming, description logics, deductive databases, and system verification, among many others. One concrete example is concept subsumption in lightweight description logics, which can be reduced to inference in propositional Horn formulae. Some problems require one to reason with inconsistent Horn formulae. this is the case when providing minimal explanations of inconsistency. this paper proposes efficient algorithms for a number of decision, function and enumeration problems related with inconsistent Horn formulae. Concretely, the paper develops efficient algorithms for finding and enumerating minimal unsatisfiable subsets (MUSes), minimal correction subsets (MCSes), but also for computing the lean kernel. the paper also shows the practical importance of some of the proposed algorithms.
the proceedings contain 39 papers. the special focus in this conference is on Optimization, Evolutionary Algorithms, Classification, Pattern Recognition, Computer Vision, Multi-agent Systems, Knowledge Representation,...
ISBN:
(纸本)9783319491295
the proceedings contain 39 papers. the special focus in this conference is on Optimization, Evolutionary Algorithms, Classification, Pattern Recognition, Computer Vision, Multi-agent Systems, Knowledge Representation, reasoning and Formal Verification. the topics include: On-line dynamic station redeployments in bike-sharing systems;efficient search of relevant structures in complex systems;flat and hierarchical classifiers for detecting emotion in tweets;spam filtering using regularized neural networks with rectified linear units;user mood tracking for opinion analysis on twitter;educational concept maps for personalized learning path generation;answer set enumeration via assumption literals;on the application of answer set programming to the conference paper assignment problem;abducing compliance of incomplete event logs;a self-adaptive context-aware group recommender system;a comparative study of inductive and transductive learning with feedforward neural networks;structural knowledge extraction from mobility data;predicting process behavior in woman;on-line learning on temporal manifolds;learning and reasoning withlogic tensor networks;probabilistic logical inference on the web;reasoning about multiple aspects in rational closure for DLs;reasoning about surprising scenarios in description logics of typicality;analysis of the impact of machine translation evaluation metrics for semantic textual similarity;spoken language understanding for service robotics in Italian;distributed and randomized dispatching and scheduling;steps in assessing a timeline-based planner;learning for verification in embedded systems and learning in physical domains.
Argumentation-based reasoning plays an important role in agent reasoning and communication. In this work, we extend an argumentation-based reasoning mechanism to take into account preferences over arguments supporting...
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ISBN:
(纸本)9781450342391
Argumentation-based reasoning plays an important role in agent reasoning and communication. In this work, we extend an argumentation-based reasoning mechanism to take into account preferences over arguments supporting contrary conclusions. Such preferences come from elements that are present or can be more easily obtained in the context of practical multi-agent programming platforms, such as multiple sources from which the information (used to construct the arguments) was acquired, as well as varying degrees of trust on them. Further, we introduce different agent profiles by varying the way certain operators are applied over the various information sources. Unlike previous approaches, our approach accounts for multiple sources for a single piece of information and is based on an argumentation-based reasoning mechanism implemented on a multi-agent platform.
We propose a declarative framework for representing and reasoning about truthfulness of agents using answer set programming. We show how statements by agents can be evaluated against a set of observations over time eq...
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this paper is a continuation and extension in developing the knowledge-based decision support design system (called HSSDR) which communicates withthe designer via drawings. Graph-based modeling of conceptualization i...
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ISBN:
(纸本)9783319393841
this paper is a continuation and extension in developing the knowledge-based decision support design system (called HSSDR) which communicates withthe designer via drawings. Graph-based modeling of conceptualization in the CAD process, which enables the system to automatically transform design drawings into appropriate graph-based data structures, is considered. Hierarchical graphs with bonds are proposed as a representation of designs. An ontological commitment between design conceptualization and internal representations of solutions, which enables us to capture intended design models, is described. Moreover, the first-order logic (FOL) of HSSDR is replaced by many-sorted FOL that makes it possible to define different sorts in specification of functions and predicates in semantics and design constraint verification.
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 answer set programming, an extended logic program may have no answer set, or only one trivial answer set. In this paper, we propose a new stable model semantics based on the restricted four-valued logic to overcome...
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ISBN:
(纸本)9783319429113;9783319429106
In answer set programming, an extended logic program may have no answer set, or only one trivial answer set. In this paper, we propose a new stable model semantics based on the restricted four-valued logic to overcome both inconsistences and incoherences in answer set programming. Our stable models coincide with classical answer sets when reasoning on consistent and coherent logic programs, and can be solved by transformation in existing ASP solvers. We also show the connection between our stable models and the extensions of default logic.
reasoning about temporal knowledge is a fundamental task in the area of artificialintelligence and knowledge representation. A key problem in this area is model checking, and indispensable for the state-of-the-art in...
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reasoning about temporal knowledge is a fundamental task in the area of artificialintelligence and knowledge representation. A key problem in this area is model checking, and indispensable for the state-of-the-art in solving this problem in large-scale settings is the technique of bounded model checking. We investigate the theoretical possibilities of this technique using parameterized complexity theory. In particular, we provide a complete parameterized complexity classification for the model checking problem for symbolically represented Kripke structures for various fragments of the temporal logics LTL, CTL and CTL*. We argue that a known result from the literature for a restricted fragment of LTL can be seen as an fpt-reduction to SAT, and show that such reductions are not possible for any of the other fragments of the temporal logics that we consider. As a by-product of our investigation, we develop a novel parameterized complexity class that can be seen as a parameterized variant of the Polynomial Hierarchy.
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