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Bridging the Gap between Reinforcement Learning and Knowledge Representation: A Logical Off- and On-Policy Framework  [PDF]
Emad Saad
Computer Science , 2010,
Abstract: Knowledge Representation is important issue in reinforcement learning. In this paper, we bridge the gap between reinforcement learning and knowledge representation, by providing a rich knowledge representation framework, based on normal logic programs with answer set semantics, that is capable of solving model-free reinforcement learning problems for more complex do-mains and exploits the domain-specific knowledge. We prove the correctness of our approach. We show that the complexity of finding an offline and online policy for a model-free reinforcement learning problem in our approach is NP-complete. Moreover, we show that any model-free reinforcement learning problem in MDP environment can be encoded as a SAT problem. The importance of that is model-free reinforcement
XML framework for concept description and knowledge representation  [PDF]
Andreas de Vries
Computer Science , 2004,
Abstract: An XML framework for concept description is given, based upon the fact that the tree structure of XML implies the logical structure of concepts as defined by attributional calculus. Especially, the attribute-value representation is implementable in the XML framework. Since the attribute-value representation is an important way to represent knowledge in AI, the framework offers a further and simpler way than the powerful RDF technology.
Comparative Study of Knowledge Representation

LIU Jian-Wei,YAN Lu-Feng,

计算机系统应用 , 2011,
Abstract: Firstly, the paper describes the concept of knowledge representation and a variety of knowledge representation. Secondly, it discusses tree levels of knowledge representation: implementational level, logical level and epistemological level. For each level, it sets a framework for comparing and evaluating intelligent knowledge representation. Then commonly-used knowledge representation schemes are compared with this framework. It is believed that this framewok can be efficiently used for comparsion and selection of nowledge representation scheme in spromblem solving.
Declarative Representation of Revision Strategies  [PDF]
Gerhard Brewka
Computer Science , 2000,
Abstract: In this paper we introduce a nonmonotonic framework for belief revision in which reasoning about the reliability of different pieces of information based on meta-knowledge about the information is possible, and where revision strategies can be described declaratively. The approach is based on a Poole-style system for default reasoning in which entrenchment information is represented in the logical language. A notion of inference based on the least fixed point of a monotone operator is used to make sure that all theories possess a consistent set of conclusions.
Product representation for default bilattices: an application of natural duality theory  [PDF]
L. M. Cabrer,A. P. K. Craig,H. A. Priestley
Computer Science , 2013,
Abstract: Bilattices (that is, sets with two lattice structures) provide an algebraic tool to model simultaneously the validity of, and knowledge about, sentences in an appropriate language. In particular, certain bilattices have been used to model situations in which information is prioritised and so can be viewed hierarchically. These default bilattices are not interlaced: the lattice operations of one lattice structure do not preserve the order of the other one. The well-known product representation theorem for interlaced bilattices does not extend to bilattices which fail to be interlaced and the lack of a product representation has been a handicap to understanding the structure of default bilattices. In this paper we study, from an algebraic perspective, a hierarchy of varieties of default bilattices, allowing for different levels of default. We develop natural dualities for these varieties and thereby obtain a concrete representation for the algebras in each variety. This leads on to a form of product representation that generalises the product representation as this applies to distributive bilattices.
Representation Theory for Default Logic  [PDF]
Victor Marek,Jan Treur,Miroslaw Truszczynski
Computer Science , 1999,
Abstract: Default logic can be regarded as a mechanism to represent families of belief sets of a reasoning agent. As such, it is inherently second-order. In this paper, we study the problem of representability of a family of theories as the set of extensions of a default theory. We give a complete solution to the representability by means of normal default theories. We obtain partial results on representability by arbitrary default theories. We construct examples of denumerable families of non-including theories that are not representable. We also study the concept of equivalence between default theories.
Representing default knowledge in biomedical ontologies: application to the integration of anatomy and phenotype ontologies
Robert Hoehndorf, Frank Loebe, Janet Kelso, Heinrich Herre
BMC Bioinformatics , 2007, DOI: 10.1186/1471-2105-8-377
Abstract: We have developed a methodology for accurately representing canonical domain ontologies within the OBO Foundry. This is achieved by adding an extension to the semantics for relationships in the biomedical ontologies that allows for treating canonical information as default. Conclusions drawn from default knowledge may be revoked when additional information becomes available. We show how this extension can be used to achieve interoperability between ontologies, and further allows for the inclusion of more knowledge within them. We apply the formalism to ontologies of mouse anatomy and mammalian phenotypes in order to demonstrate the approach.Biomedical ontologies require a new class of relations that can be used in conjunction with default knowledge, thereby extending those currently in use. The inclusion of default knowledge is necessary in order to ensure interoperability between ontologies.As the volume of biomedical data and knowledge presented in scientific papers increases, there is an increasing need to support formal analyses of these data and to pre-process knowledge for further use in solving problems and developing and testing hypotheses. The precise capture of biological data and knowledge and their correct and consistent representation in computational form is a basic pre-requisite for achieving these goals. Ontologies may provide a basis for integrating, processing and applying biomedical data. Their integration into a common ontological framework is an indispensible step towards the development of expressive knowledge bases. Interoperability between these ontologies would facilitate the consistent use of biomedical data in the form of annotations, allow for queries over multiple ontologies and form a rich knowledge resource for biomedicine that could be further used in solving problems and stating hypotheses. Different ontologies have been developed by different groups with different intentions. As a result, translating a statement or transferring an a
Advances in the Logical Representation of Lexical Semantics  [PDF]
Bruno Mery,Christian Retoré
Computer Science , 2013,
Abstract: The integration of lexical semantics and pragmatics in the analysis of the meaning of natural lan- guage has prompted changes to the global framework derived from Montague. In those works, the original lexicon, in which words were assigned an atomic type of a single-sorted logic, has been re- placed by a set of many-facetted lexical items that can compose their meaning with salient contextual properties using a rich typing system as a guide. Having related our proposal for such an expanded framework \LambdaTYn, we present some recent advances in the logical formalisms associated, including constraints on lexical transformations and polymorphic quantifiers, and ongoing discussions and research on the granularity of the type system and the limits of transitivity.
An Abductive Framework for Horn Knowledge Base Dynamics  [PDF]
Radhakrishnan Delhibabu
Computer Science , 2014,
Abstract: The dynamics of belief and knowledge is one of the major components of any autonomous system that should be able to incorporate new pieces of information. We introduced the Horn knowledge base dynamics to deal with two important points: first, to handle belief states that need not be deductively closed; and the second point is the ability to declare certain parts of the belief as immutable. In this paper, we address another, radically new approach to this problem. This approach is very close to the Hansson's dyadic representation of belief. Here, we consider the immutable part as defining a new logical system. By a logical system, we mean that it defines its own consequence relation and closure operator. Based on this, we provide an abductive framework for Horn knowledge base dynamics.
Logical Object as a Basis of Knowledge Based Systems
Xu Dianxiang,Zheng Guoliang,
Xu Dianxiang
,Zheng Guoliang

计算机科学技术学报 , 1995,
Abstract: This paper presents a framework called logical knowledge object (LKO),which is taken as a basis of the dependable development of knowledge based systems(KBSs). LKO combines logic programming and object-oriented programming paradigms, where objects are viewed as abstractions with states,constraints, behaviors and inheritance. The operational semantics defined in the style of natural semantics is simple and clear. A hybrid knowledge represen-tation amalgamating rule, frame, semantic network and blackboard is available for both most structured and flat knowledge. The management of knowledge bases has been formally specified. Accordingly, LKO is well suited for the formal representation of knowledge and requirements of KBSs. Based on the framework, verification techniques are also explored to enhance the analysis of requirement specifications and the validation of KBSs. In addition, LKO pro-vides a methodology for the development of KBSs, applying the concepts of rapid prototyping and top-down design to deal with changing and incomplete requirements, and to provide multiple abstract models of the domain, where formal methods might be used at each abstract level.
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