Lifestyle-related diseases can be reduced by making daily dietary choices. Functional components in foods have the potential to provide benefits in this regard. We constructed a knowledge graph that connects the funct...
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ISBN:
(纸本)9798350385359
Lifestyle-related diseases can be reduced by making daily dietary choices. Functional components in foods have the potential to provide benefits in this regard. We constructed a knowledge graph that connects the functional components of foods to recipes, and developed a recommendation system to suggest dishes that may help alleviate lifestyle-related diseases. As dietary requirements vary widely depending on specific diseases and individual conditions, these requirements are combined to form a vast probability distribution. Our proposed system uses probabilistic logicprogramming to generate recommendations that are based on disease-specific dietary requirements, using a knowledge graph of foods and information about the user's condition. In the proposed method, nodes in the knowledge graph, such as food functionality or recipes, are characterized by their relationships with other surrounding nodes, such as ingredients. We conducted an experiment to suggest recipes specifically for patients with diabetes and dyslipidemia. At the result, our system enable to recommend numerous recipes beneficial for the improvement of lifestyle-related diseases, especially for users with diabetes, with a precision of over 0.99.
We will discuss about the intelligent multi-agent based convergence system in AI. the multi-agent concept is varied from 2 or 3 agents to many agents. therefore, to construct the appropriate concept which you want to ...
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ISBN:
(纸本)9781424435968
We will discuss about the intelligent multi-agent based convergence system in AI. the multi-agent concept is varied from 2 or 3 agents to many agents. therefore, to construct the appropriate concept which you want to implement is more important. In this paper, we will discuss the concept of multi-agent, and discuss some application areas of fuzzy logic based multi-agent, especially in bioinformatics and digital library etc. And finally we will discuss about the future research areas of multi-agent in AI.
An important goal of research in description logics (DLs) and related logic-based KR formalisms is to identify the worst-case complexity of reasoning. Such results, however, measure the complexity of a logic as a whol...
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ISBN:
(纸本)9783642287176
An important goal of research in description logics (DLs) and related logic-based KR formalisms is to identify the worst-case complexity of reasoning. Such results, however, measure the complexity of a logic as a whole. For example, reasoning in the basic DL ALCI\mathcal{ALCI} is ExpTime-complete, which means that ALCI\mathcal{ALCI} constructors can be used in a way so that exponential time is strictly required for solving a reasoning problem. It is, however, well known that, given two ALCI\mathcal{ALCI} knowledge bases of roughly the same size, reasoning with one knowledge base may be much more difficult than withthe other, depending on the interaction of the axioms in the KBs. thus, existing worst-case complexity results provide only a very coarse measure of reasoning complexity, and they do not tell us much about the “hardness” of each individual knowledge base.
In this paper, we present the Enfragmo system for specifying and solving combinatorial search problems. It supports natural specification of problems by providing users with a rich language, based on an extension of f...
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ISBN:
(纸本)9783642287176
In this paper, we present the Enfragmo system for specifying and solving combinatorial search problems. It supports natural specification of problems by providing users with a rich language, based on an extension of first order logic. Enfragmo takes as input a problem specification and a problem instance and produces a propositional CNF formula representing solutions to the instance, which is sent to a SAT solver. Because the specification language is high level, Enfragmo provides combinatorial problem solving capability to users without expertise in use of SAT solvers or algorithms for solving combinatorial problems. Here, we describe the specification language and implementation of Enfragmo, and give experimental evidence that its performance is comparable to that of related systems.
Despite the availability of both multithreading and tabling in some Prolog systems, the implementation of these two features, such that they work together, implies complex ties to one another and to the underlying eng...
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ISBN:
(纸本)9781467345651;9780769549033
Despite the availability of both multithreading and tabling in some Prolog systems, the implementation of these two features, such that they work together, implies complex ties to one another and to the underlying engine. In recent work, we have proposed an approach to combine multithreading with tabling, implemented on top of the Yap Prolog system, whose primary goal was to reduce memory usage for the table space. Regarding the execution times, we observed some problems related to Yap's memory allocator, which is based on the operating system's default memory allocator, when running programs that allocate a higher number of data structures in the table space. In this paper, we propose a more efficient and scalable memory allocator for multithreaded tabled evaluation of logic programs. Our goal is to minimize the performance degradation that the system suffers when it is exposed to simultaneous memory requests made by multiple threads. For that, we propose a memory allocator based on local and global pages, to split memory among specific data structures and different threads, together with a strategy where data structures of the same type are pre-allocated within a page. Experimental results show that our new memory allocator can effectively reduce the execution time and scale better, when increasing the number of threads, than the original allocator.
Medial is an inference rule scheme that appears in various deductive systems based on deep inference. In this paper we investigate the properties of medial as rewriting rule independently from logic. We present a grap...
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ISBN:
(纸本)9783540734475
Medial is an inference rule scheme that appears in various deductive systems based on deep inference. In this paper we investigate the properties of medial as rewriting rule independently from logic. We present a graph theoretical criterion for checking whether there exists a medial rewriting path between two formulas. Finally, we return to logic and apply our criterion for giving a combinatorial proof for a decomposition theorem, i.e., proof theoretical statement about syntax.
Markov Chain Monte Carlo (MCMC) methods are a class of algorithms used to perform approximate inference in probabilistic models. When direct sampling from a probability distribution is difficult, MCMC algorithms provi...
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ISBN:
(纸本)9783030351663;9783030351656
Markov Chain Monte Carlo (MCMC) methods are a class of algorithms used to perform approximate inference in probabilistic models. When direct sampling from a probability distribution is difficult, MCMC algorithms provide accurate results by constructing a Markov chain that gradually approximates the desired distribution. In this paper we describe and compare the performances of two MCMC sampling algorithms, Gibbs sampling and Metropolis Hastings sampling, with rejection sampling for probabilistic logic programs. In particular, we analyse the relation between execution time and number of samples and how fast each algorithm converges.
In this paper we present goal-directed deduction methods for Lukasiewicz infinite-valued logic L, giving logicprogramming style algorithms which both have a logical interpretation and provide a suitable basis for imp...
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ISBN:
(纸本)3540230246
In this paper we present goal-directed deduction methods for Lukasiewicz infinite-valued logic L, giving logicprogramming style algorithms which both have a logical interpretation and provide a suitable basis for implementation. We begin by considering a basic version with connections to calculi for other logics, then make refinements to obtain greater efficiency and termination properties, and to deal with further connectives and truth constants. We finish by considering applications of these algorithms to fuzzy logicprogramming.
the paper introduces the SILK tool-set, a tool-set based on constraint logicprogramming techniques for the support of application integration. We focus on the Integrator component of SILK, which provides tools and te...
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ISBN:
(纸本)3540439307
the paper introduces the SILK tool-set, a tool-set based on constraint logicprogramming techniques for the support of application integration. We focus on the Integrator component of SILK, which provides tools and techniques to support the process of model evolution: unification of the models of the information sources and their mapping Onto the conceptual models of their user-groups. We present the basic axchitecture of SILK and introduce the SILK Knowledge Base, which stores the meta-information describing the information sources. the SILK Knowledge Base can contain both object-oriented and ontology-based descriptions, annotated with constraints. the constraints can be used both for expressing the properties of the objects and for providing mappings between them. We give a brief introduction to SILan, the language for Knowledge Base presentation and maintenance. We describe the implementation status of SILK and give a simple example, which shows how constraints and constraint reasoning techniques can be used to support model evolution.
this book constitutes the proceedings of the 18thinternationalconference on logic for programming, Artificial Intelligence, and Reasoning, LPAR-18, held in Merida, Venezuela, in March 2012. the 25 regular papers and...
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ISBN:
(数字)9783642287176
ISBN:
(纸本)9783642287169
this book constitutes the proceedings of the 18thinternationalconference on logic for programming, Artificial Intelligence, and Reasoning, LPAR-18, held in Merida, Venezuela, in March 2012. the 25 regular papers and 6 tool descriptions and experimental papers presented were carefully reviewed and selected from 74 submissions.
the series of internationalconferences on logic for programming, Artificial Intelligence and Reasoning (LPAR) is a forum where, year after year, some of the most renowned researchers in the areas of logic, automated reasoning, computational logic, programming languages and their applications come to present cutting-edge results, to discuss advances in these fields, and to exchange ideas in a scientifically emerging part of the world.
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