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expansion not maximum product is nets for entropy. probabilities conditional of belief The
The product expansion of conditional probabilities for belief nets is not maximum entropy.
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for a model. to of deny kind appears This assurance desirable the
This appears to deny a desirable kind of assurance for the model.
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of concept to is generalization, thc of described. specialization, concept The dual
The concept of generalization, dual to thc concept of specialization, is described.
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Mukaidono's is described. system reason A fuzzy an maintenance which ATMS extends through logic
A reason maintenance system which extends an ATMS through Mukaidono's fuzzy logic is described.
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to distribution maximum entropy given The derives the subject a constraints. procedure
The procedure derives a maximum entropy distribution subject to the given constraints.
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raises multiple-author of interesting questions. of more variety The a settings introduction sophisticated
The introduction of more sophisticated multiple-author settings raises a variety of interesting questions.
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nature of consensus. involves the question and One compromise such
One such question involves the nature of compromise and consensus.
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in introduces prior setting. This net a Bayes paper compromises
This paper introduces prior compromises in a Bayes net setting.
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notions (VBS). systems valuation-based the paper and independence introduces in of This conditional independence
This paper introduces the notions of independence and conditional independence in valuation-based systems (VBS).
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axiomatic framework uncertainty many is capable an different representing VBS calculi. of
VBS is an axiomatic framework capable of representing many different uncertainty calculi.
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independence define joint valuation. of and of conditional We the independence terms in factorization
We define independence and conditional independence in terms of factorization of the joint valuation.
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relationship The is databases examined. relational between and networks belief
The relationship between belief networks and relational databases is examined.
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diagrams. using a and is formulated influence as modeled reasoning sequential process, stochastic is Diagnostic
Diagnostic reasoning is formulated as a sequential stochastic process, and is modeled using influence diagrams.
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decision uses thresholds sensitivity analysis. approach class the for provide DYNASTY to equivalence an
DYNASTY uses an equivalence class approach to provide decision thresholds for the sensitivity analysis.
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to different. only equivalence-class actions reasoning differentiates diagnoses required This if are diagnostic the approach
This equivalence-class approach to diagnostic reasoning differentiates diagnoses only if the required actions are different.
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dynamically for algorithms updating of A set are network-topology necessary. the network when proposed updating
A set of network-topology updating algorithms are proposed for dynamically updating the network when necessary.
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to is applied layered hierarchies. distinct strategy the set Hence a control of
Hence the control strategy is applied to a layered set of distinct hierarchies.
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with with a clause presents abduction, Horn framework for probabilities paper This simple hypotheses. associated
This paper presents a simple framework for Horn clause abduction, with probabilities associated with hypotheses.
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consultants; consultation attempt of capability emulate We human systems. this to computer in
We attempt to emulate this capability of human consultants; in computer consultation systems.
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for Our been in use systems. developed consultation has task-oriented mechanism
Our mechanism has been developed for use in task-oriented consultation systems.
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a The travel for agency. domain is chosen of we that that exploration have
The domain that we have chosen for exploration is that of a travel agency.
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past of intensive for the Learning study has the decade. subject Ontology been
Ontology Learning has been the subject of intensive study for the past decade.
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formal precise more compared Heavy-weight Ontology ontology to reasoning learning. when logic-based statistical supports Learning
Heavy-weight Ontology Learning supports more precise formal logic-based reasoning when compared to statistical ontology learning.
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IS-A evaluation adopted on based Standard We rich Gold Learning Ontology Wikipedia chosen documents. have
We have adopted Gold Standard based Ontology Learning evaluation on chosen IS-A rich Wikipedia documents.
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relations concepts between and models semantic logic. based fuzzy of examine similarity Finally, these we
Finally, we examine relations between these concepts and similarity based semantic models of fuzzy logic.
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performing. are usually the The they uncertainty way on changes experts depending manage task
The way experts manage uncertainty usually changes depending on the task they are performing.
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arguments example, well-known. ?consistent are behavior' betting For
For example, ?consistent betting behavior' arguments are well-known.
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models. paper probability another present explores for rationale The
The present paper explores another rationale for probability models.
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on can build of we sand? castle What kind
What kind of castle can we build on sand?
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last for generations. set designed foundations our to on We bedrock, want
We want our foundations set on bedrock, designed to last for generations.
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directed relationships of among random graphs independence representing set variables. acyclic Bayesian networks are a
Bayesian networks are directed acyclic graphs representing independence relationships among a set of random variables.
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exhaustive be as can of exclusive mutually A regarded and propositions. variable set random a
A random variable can be regarded as a set of exhaustive and mutually exclusive propositions.
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introspect about to must probabilities so error, subject their Such the planner are validity.
Such probabilities are subject to error, so the planner must introspect about their validity.
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can these be about statistics. events the probability using made of Inferences
Inferences about the probability of these events can be made using statistics.
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can the Inferences estimation. interval about of the using made approximations be validity
Inferences about the validity of the approximations can be made using interval estimation.
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inference are A and relevant set of patterns knowledge types identified.
A relevant set of inference patterns and knowledge types are identified.
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technique al. (Shafer The local computation et
The local computation technique (Shafer et al.
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expressed is Uncertain parameterized operators. means by modal of information
Uncertain information is expressed by means of parameterized modal operators.
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We and this and propose sound axiomatization. complete logic a give semantics for multimodal a
We propose a semantics for this multimodal logic and give a sound and complete axiomatization.
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beliefs analyzed. unnormalized The nature these is of
The nature of these unnormalized beliefs is analyzed.
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the used experts. decision structure by be to provided synthesize An the interval rules can
An interval structure can be used to synthesize the decision rules provided by the experts.
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expressed interval prescribed proportions. term of a is as Each linguistic
Each linguistic term is expressed as a prescribed interval of proportions.
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The modelling studied rules, context. quantified this of in syllogism, the probabilistic chaining is
The quantified syllogism, modelling the chaining of probabilistic rules, is studied in this context.
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Irrelevance-based domain-independent for are using useful partial MAPs networks. constructs belief explanation
Irrelevance-based partial MAPs are useful constructs for domain-independent explanation using belief networks.
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tool, modeling. a is proposed this In for new environment called paper, U-yraph,
In this paper, a new tool, called U-yraph, is proposed for environment modeling.
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report opportunities in an beliefnet parallelism inference. for investigation We into on experimental
We report on an experimental investigation into opportunities for parallelism in beliefnet inference.
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clustering the parallelism find tree, at opportunity for negligible level. We or topological,
We find negligible opportunity for parallelism at the topological, or clustering tree, level.
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to operate network queries. answer over inference algorithms the Probabilistic
Probabilistic inference algorithms operate over the network to answer queries.
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paper independence paradigms Bayesian asymmetric for networks representation encoding assertions. discuses This multiple
This paper discuses multiple Bayesian networks representation paradigms for encoding asymmetric independence assertions.
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method proposes problems. paper a solving new decision Bayesian for This
This paper proposes a new method for solving Bayesian decision problems.
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that obtained identical to from homogeneous those are be Probabilities the network. obtained would
Probabilities obtained are identical to those that would be obtained from the homogeneous network.
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propagation shift and discuss acquired evidence. previously We to junction of different a attention tree
We discuss attention shift to a different junction tree and propagation of previously acquired evidence.
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for systems. adaptive aHUGIN, creating paper a describes tool The
The paper describes aHUGIN, a tool for creating adaptive systems.
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reported is are a session experiments the with Finally and results discussed.
Finally a session with experiments is reported and the results are discussed.
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discussed. belief propagation are Several situations of
Several situations of belief propagation are discussed.
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discriminate information. between and priori' We 'a evidential
We discriminate between 'a priori' and evidential information.
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methods them. Then, we each combination for of propose different one
Then, we propose different combination methods for each one of them.
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We and conditioning combination information. evidential the 'a heterogeneous of also consider as priori'
We also consider conditioning as the heterogeneous combination of 'a priori' and evidential information.
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The evidential represented as a convex set information of is likelihood functions.
The evidential information is represented as a convex set of likelihood functions.
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classical These to distribution with an Possibility possibility Theory. according have associated behavior will
These will have an associated possibility distribution with behavior according to classical Possibility Theory.
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distribution the methods used an to derive for statistic. Asymptotic test are approximate
Asymptotic methods are used to derive an approximate distribution for the test statistic.
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result The VT that in the among achieved is them accuracy best both experiments. parsing
The result is that VT achieved the best parsing accuracy among them in both experiments.
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superior such in found not that does necessarily yield performance. case a We VT
We found that in such a case VT does not necessarily yield superior performance.
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Practice and To (TPLP). Theory Logic of Programming in appear
To appear in Theory and Practice of Logic Programming (TPLP).
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overcome preferential difficulties. of (RPMs) to work models promises on ranked these some Recent
Recent work on ranked preferential models (RPMs) promises to overcome some of these difficulties.
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adequate RPMs belief show change. to not iterated handle we Here are that
Here we show that RPMs are not adequate to handle iterated belief change.
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always allow the for Specifically, not belief reversibility we RPMs show of that change. do
Specifically, we show that RPMs do not always allow for the reversibility of belief change.
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result belief. the indicates need This strengths numerical for of
This result indicates the need for numerical strengths of belief.
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problems decision and uncertainty discuss representation. for making Bayesian We convex
We discuss problems for convex Bayesian decision making and uncertainty representation.
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a as been with for Possibilistic proposed reasoning has formalism uncertainty. logic numerical
Possibilistic logic has been proposed as a numerical formalism for reasoning with uncertainty.
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networks of representation Influence with a uncertainty. diagram belief is graphical
Influence diagram is a graphical representation of belief networks with uncertainty.
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probabilistic studies model diagram. properties the influence This structural in an article of a
This article studies the structural properties of a probabilistic model in an influence diagram.
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controllability observability developed structural formulated. algorithms theorems theorems are and structural In are particular, and
In particular, structural controllability theorems and structural observability theorems are developed and algorithms are formulated.
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system determined by be properties the Both of can ranks the matrices.
Both properties can be determined by the ranks of the system matrices.
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described. of is Monte-Carlo the belief calculation computationally-efficient Dempster-Shafer for algorithm very A
A very computationally-efficient Monte-Carlo algorithm for the calculation of Dempster-Shafer belief is described.
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decision is the complicated making knowledge involved. the often complexity Automated of by
Automated decision making is often complicated by the complexity of the knowledge involved.
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sensitive the Much complexity context phenomena. variations of from of arises underlying this the
Much of this complexity arises from the context sensitive variations of the underlying phenomena.
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for We framework a descriptive, propose context-sensitive knowledge. representing
We propose a framework for representing descriptive, context-sensitive knowledge.
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uncertain knowledge a approach attempts integrate to Our and categorical network formalism. in
Our approach attempts to integrate categorical and uncertain knowledge in a network formalism.
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representations quantitative studied qualitative was in theory. extensively compatibility and The of probability of beliefs
The compatibility of quantitative and qualitative representations of beliefs was studied extensively in probability theory.
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with is of qualitative the shown compatible probability belief functions. that It structure is monotonic
It is shown that the structure of qualitative probability is compatible with monotonic belief functions.
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control and model dynamic construction failure of is to necessary also revision. Diagnosis model
Diagnosis of model failure is also necessary to control dynamic model construction and revision.
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We to a represent distribution labelings use labeling. over of each respective possibilities possibility
We use a possibility distribution over labelings to represent respective possibilities of each labeling.
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the a of each certainty of simple expression respective allow constraint. Necessity-valued degrees constraints
Necessity-valued constraints allow a simple expression of the respective certainty degrees of each constraint.
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approach is technical of The main our advantage the framework. integration CSP in its
The main advantage of our approach is its integration in the CSP technical framework.
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simple a demonstrated our The design on of utility is approach problem.
The utility of our approach is demonstrated on a simple design problem.
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to the are added evidence. specific of form in DBN Sensor basic observations the
Sensor observations are added to the basic DBN in the form of specific evidence.
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sensor However, often is incorrect. or data partially totally
However, sensor data is often partially or totally incorrect.
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conditional with incrementally. probabilities for and rules independences Uncertain explicit maintained be bounds can
Uncertain rules with bounds for probabilities and explicit conditional independences can be maintained incrementally.
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new precise particular, for entailment. bounds probabilistic In we analytical provide
In particular, we provide new precise analytical bounds for probabilistic entailment.
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syntactically such Nevertheless, inferences and be characterized can both semantically.
Nevertheless, such inferences can be characterized both syntactically and semantically.
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by matrices. The controlled flow mass specialization is
The mass flow is controlled by specialization matrices.
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aspects be matrices. reasoning represented Even can certain by specialization of non-monotonic some
Even some aspects of non-monotonic reasoning can be represented by certain specialization matrices.
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the reasoning representing about utility knowledge agent's actions. and with an We time-dependent of discuss
We discuss representing and reasoning with knowledge about the time-dependent utility of an agent's actions.
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consistency is The base knowledge the analyzed. of
The consistency of the knowledge base is analyzed.
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We knowledge representation needed first the and solving describe formalisms the problem, problem paradigms.
We first describe the problem, the needed knowledge representation formalisms and problem solving paradigms.
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can blackboard approach a clearly explained system system's be The from interactive perspective.
The system's interactive approach can be clearly explained from a blackboard system perspective.
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chronic techniques. marker-passing Useless paths for are problem a
Useless paths are a chronic problem for marker-passing techniques.
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discussed. are point to the of probabilities estimates Techniques for posterior sentences entailed calculate
Techniques to calculate point estimates for the posterior probabilities of entailed sentences are discussed.
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inference. on We review algorithms randomized for previous probabilistic BNRAS work algorithms- approximation
We review previous work on BNRAS algorithms- randomized approximation algorithms for probabilistic inference.
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