this paper is focused on looking for an appropriate coherence notion which allows us to deal with inconsistent information included in multi-adjoint normal logic programs. Different definitions closely related to the ...
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In answer-set programming (ASP), the main focus usually is on computing answer sets which correspond to solutions to the problem represented by a logic program. Simple reasoning over answer sets is sometimes supported...
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We examine how well the state-of-the-art (SOTA) models used in legal reasoning support abductive reasoning tasks. Abductive reasoning is a form of logical inference in which a hypothesis is formulated from a set of ob...
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We examine how well the state-of-the-art (SOTA) models used in legal reasoning support abductive reasoning tasks. Abductive reasoning is a form of logical inference in which a hypothesis is formulated from a set of observations, and that hypothesis is used to explain the observations. the ability to formulate such hypotheses is important for lawyers and legal scholars as it helps them articulate logical arguments, interpret laws, and develop legal theories. Our motivation is to consider the belief that deep learning models, especially large language models (LLMs), will soon replace lawyers because they perform well on tasks related to legal text processing. But to do so, we believe, requires some form of abductive hypothesis formation. In other words, while LLMs become more popular and powerful, we want to investigate their capacity for abductive reasoning. To pursue this goal, we start by building a logic-augmented dataset for abductive reasoning with 498,697 samples and then use it to evaluate the performance of a SOTA model in the legal field. Our experimental results show that although these models can perform well on tasks related to some aspects of legal text processing, they still fall short in supporting abductive reasoning tasks. 2023 Copyright for this paper by its authors.
the need for a more autonomous management of distributed systems and networks has driven research and industry to look for management frameworks that go beyond the direct manipulation of network devices and systems. O...
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ISBN:
(纸本)9783540721994
the need for a more autonomous management of distributed systems and networks has driven research and industry to look for management frameworks that go beyond the direct manipulation of network devices and systems. One approach towards this aim is to build policy-based management systems. Policy-based computing refers to a software paradigm developed around the concept of building autonomous systems that provide system administrators and decision makers with interfaces that let them set general guiding principles and policies to govern the behavior and interactions of the managed systems. Although many of the tasks are still carried out manually and ad hoc, instances of limited policy-based systems can be found in areas such as Internet service management, privacy, security and access management, management of quality of service and service level agreements in networks. Policies can be specified at many levels of abstraction, from natural language specifications to more elementary condition-action rule specifications. From these specifications policy systems need to come up with implementations. Some of these implementations can be done automatically, others require manual steps. In some cases policies impose legal commitments and systems should be able to demonstrate compliance. there are also situations in which policies are in conflict with each other and a system cannot implement them simultaneously without providing methods for conflict resolution. In this presentation I will review a few policy systems, applications and specification languages. then I will provide a more formal characterization of policies and their computational model. I will show a simple policy language in the style of the action description language A. I will discuss current solutions to policy conflicts, discuss the problem of policy refinement, i.e. transformations from high level specifications to lower level specifications, current approaches to refinement and provide a partial formal
this book constitutes the refereed proceedings of the 15th IFIP WG 12.5 internationalconference on Artificial Intelligence Applications and Innovations, AIAI 2019, held in Hersonissos, Crete, Greece, in May 2019.;the...
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ISBN:
(数字)9783030198237
ISBN:
(纸本)9783030198220
this book constitutes the refereed proceedings of the 15th IFIP WG 12.5 internationalconference on Artificial Intelligence Applications and Innovations, AIAI 2019, held in Hersonissos, Crete, Greece, in May 2019.;the 49 full papers and 6 short papers presented were carefully reviewed and selected from 101 submissions. they cover a broad range of topics such as deep learning ANN; genetic algorithms - optimization; constraints modeling; ANN training algorithms; social media intelligent modeling; text mining/machine translation; fuzzy modeling; biomedical and bioinformatics algorithms and systems; feature selection; emotion recognition; hybrid Intelligent models; classification - pattern recognition; intelligent security modeling; complex stochastic games; unsupervised machine learning; ANN in industry; intelligent clustering; convolutional and recurrent ANN; recommender systems; intelligent telecommunications modeling; and intelligent hybrid systems using Internet of things. the papers are organized in the following topical sections:;AI anomaly detection - active learning; autonomous vehicles - aerial vehicles; biomedical AI; classification - clustering; constraint programming - brain inspired modeling; deep learning - convolutional ANN; fuzzy modeling; learning automata - logic based reasoning; machine learning - natural language; multi agent - IoT; nature inspired flight and robot; control - machine vision; and recommendation systems.
Modelling is becoming a necessity in studying biological signalling pathways, because the combinatorial complexity of such systems rapidly overwhelms intuitive and qualitative forms of reasoning. Yet, this same combin...
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ISBN:
(纸本)9783540744061
Modelling is becoming a necessity in studying biological signalling pathways, because the combinatorial complexity of such systems rapidly overwhelms intuitive and qualitative forms of reasoning. Yet, this same combinatorial explosion makes the traditional modelling paradigm based on systems of differential equations impractical. In contrast, agent-based or concurrent languages, such as kappa. [1,2,3] or the closely related BioNetGen language [4,5,6,7,8,9,10], describe biological interactions in terms of rules, thereby avoiding the combinatorial explosion besetting differential equations. Rules are expressed in an intuitive graphical form that transparently represents biological knowledge. In this way, rules become a natural unit of model building, modification, and discussion. We illustrate this with a sizeable example obtained from refactoring two models of EGF receptor signalling that are based on differential equations [11,12]. An exciting aspect of the agent-based approach is that it naturally lends itself to the identification and analysis of the causal structures that deeply shape the dynamical, and perhaps even evolutionary, characteristics of complex distributed biological systems. In particular, one can adapt the notions of causality and conflict, familiar from con-currency theory, to kappa, our representation language of choice. Using the EGF receptor model as an example, we show how causality enables the formalization of the colloquial concept of pathway and, perhaps more surprisingly, how conflict can be used to dissect the signalling dynamics to obtain a qualitative handle on the range of system behaviours. By taming the combinatorial explosion, and exposing the causal structures and key kinetic junctures in a model, agent- and rule-based representations hold promise for making modelling more powerful, more perspicuous, and of appeal to a wider audience.
State of the art analyzers in the logicprogramming (LP) paradigm are nowadays mature and sophisticated. they allow inferring a wide variety of global properties including termination, bounds on resource consumption, ...
ISBN:
(纸本)9783540696087
State of the art analyzers in the logicprogramming (LP) paradigm are nowadays mature and sophisticated. they allow inferring a wide variety of global properties including termination, bounds on resource consumption, etc. the aim of this work is to automatically transfer the power of such analysis tools for LP to the analysis and verification of Java bytecode (jvml). In order to achieve our goal, we rely on well-known techniques for meta-programming and program specialization. More precisely, we propose to partially evaluate a jvml interpreter implemented in LP together with (an LP representation of) a jvml program and then analyze the residual program. Interestingly, at least for the examples we have studied, our approach produces very simple LP representations of the original jvml programs. this can be seen as a decompilation from jvml to high-level LP source. By reasoning about such residual programs, we can automatically prove in the CiaoPP system some non-trivial properties of jvml programs such as termination, run-time error freeness and infer bounds on its resource consumption. We are not aware of any other system which is able to verify such advanced properties of Java bytecode.
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