text stringlengths 27 153 | label stringlengths 27 153 | id int64 0 40k |
|---|---|---|
neither nor knowledge rule-based requires It of is tools. new frame-based, system and a engineering | It is neither rule-based nor frame-based, and requires a new system of knowledge engineering tools. | 7,100 |
with interval-valued looks at essay decision-making measures. probability This | This essay looks at decision-making with interval-valued probability measures. | 7,101 |
information. implement we more approach, order epistemological need to In the | In order to implement the approach, we need more epistemological information. | 7,102 |
solution a the procedures to The provide problem uncertain spatial relative relationships. of general estimating | The procedures provide a general solution to the problem of estimating uncertain relative spatial relationships. | 7,103 |
the all mode. using (These Bayes are procedures, | (These are all Bayes procedures, using the mode. | 7,104 |
in has systems reasoning often expert calculi. used ad-hoc Evidential uncertainty | Evidential reasoning in expert systems has often used ad-hoc uncertainty calculi. | 7,105 |
higher order applied deals reasoning. probabilities Metaprobability to theory with evidential | Metaprobability theory deals with higher order probabilities applied to evidential reasoning. | 7,106 |
features has possible values, Each of three the (e.g. two | Each of the three features has two possible values, (e.g. | 7,107 |
from sensor Beliefs and sensor are accrued A, two B. formed from sensors: evidence | Beliefs are formed from evidence accrued from two sensors: sensor A, and sensor B. | 7,108 |
Each defining corresponding sensor feature. the senses | Each sensor senses the corresponding defining feature. | 7,109 |
that third feature observed the by is any sensor. Note not | Note that the third feature is not observed by any sensor. | 7,110 |
General analyzing considered. a are database in information in probabilistic problems | General problems in analyzing information in a probabilistic database are considered. | 7,111 |
represent tree (hidden) conceptual Internal nodes inaccessible variables to observation. of the | Internal nodes of the tree represent conceptual (hidden) variables inaccessible to observation. | 7,112 |
to remains imprecisions. method incremental, is and local, described efficient, The robust measurement | The method described is incremental, local, efficient, and remains robust to measurement imprecisions. | 7,113 |
genome-scale network of created We metabolism. have a reconstruction coli Escherichia | We have created a genome-scale network reconstruction of Escherichia coli metabolism. | 7,114 |
moves the programs procedure. choosing approach is traditional game-playing in to The minimax | The traditional approach to choosing moves in game-playing programs is the minimax procedure. | 7,115 |
is increasing search its general that depth improves use play. underlying belief The | The general belief underlying its use is that increasing search depth improves play. | 7,116 |
tree This game called pathology. phenomenon is | This phenomenon is called game tree pathology. | 7,117 |
the This strengthen depth uniform causes hypothesis pathology. property two that points that raises win | This property raises two points that strengthen the hypothesis that uniform win depth causes pathology. | 7,118 |
This the the evaluation predicts of pathological original failing function. behavior | This failing predicts the pathological behavior of the original evaluation function. | 7,119 |
by temporal setting is the compounded factory uncertainty. in Scheduling computational complexity and | Scheduling in the factory setting is compounded by computational complexity and temporal uncertainty. | 7,120 |
hypotheses the Often, evidence hierarchical in and nature. are | Often, the evidence and hypotheses are hierarchical in nature. | 7,121 |
other logic of same Bayesian approach. the has reasoning limitations This probabilistic systems the of | This logic has the same limitations of other probabilistic reasoning systems of the Bayesian approach. | 7,122 |
consistency very not common reasoning, sense assumption. is For natural a | For common sense reasoning, consistency is not a very natural assumption. | 7,123 |
this propose we the In logic. of some shall probabilistic paper, extensions | In this paper, we shall propose some extensions of the probabilistic logic. | 7,124 |
not. all the we space section, consistent the In interpretations, second or shall consider of | In the second section, we shall consider the space of all interpretations, consistent or not. | 7,125 |
interval is its each Pls(s)]. [Spt(s), proposition belief For by function an represented s, | For each proposition s, its belief function is represented by an interval [Spt(s), Pls(s)]. | 7,126 |
to logic restricting probabilistic get Certainly, we consistent interpretations. by further Nilsson's | Certainly, we get Nilsson's probabilistic logic by further restricting to consistent interpretations. | 7,127 |
probabilistic of the theory. the framework probability brings interpretation into This logic | This interpretation brings the probabilistic logic into the framework of probability theory. | 7,128 |
have probability We distribution for proposition. each a | We have a probability distribution for each proposition. | 7,129 |
(marginal), conditional joint absolute We probability and compute may distributions. | We may compute absolute (marginal), conditional and joint probability distributions. | 7,130 |
of subsets probabilities, we propositions or get probabilities individual joint appropriate propositions. of summing By | By summing appropriate joint probabilities, we get probabilities of individual propositions or subsets of propositions. | 7,131 |
In relaxation scheme logic. consider a shall for section, we probabilistic last the | In the last section, we shall consider a relaxation scheme for probabilistic logic. | 7,132 |
problem idea main consistent vision. the in from arises computer The labeling | The main idea arises from the consistent labeling problem in computer vision. | 7,133 |
is to applied This originally scene drawings. line analysis of method | This method is originally applied to scene analysis of line drawings. | 7,134 |
are Explanation expert of facilities frameworks. particularly a system feature important | Explanation facilities are a particularly important feature of expert system frameworks. | 7,135 |
in had rule-based results. It traditional area which an have mixed is frameworks expert system | It is an area in which traditional rule-based expert system frameworks have had mixed results. | 7,136 |
this effect We in that measure operating context any satisfy argue certain properties. must | We argue that any effect measure operating in this context must satisfy certain properties. | 7,137 |
by population coalescent-based proposed rooted A tree et Nielsen model, al. originally | A coalescent-based rooted population tree model, originally proposed by Nielsen et al. | 7,138 |
never model However, the been of proven. has identifiability this | However, the identifiability of this model has never been proven. | 7,139 |
probability using version simplified and independence assumptions. conditional a of | and a simplified version of probability using conditional independence assumptions. | 7,140 |
Importance of how ranked. the quantitatively We assessed biases illustrate may and be | We illustrate how the Importance of biases may be quantitatively assessed and ranked. | 7,141 |
given critical for a is UlS's of robustness application. selecting factor Considerations a might be | Considerations of robustness might be a critical factor is selecting UlS's for a given application. | 7,142 |
calculus (e.g. or certainty a factors), probabilities | probabilities or certainty factors), a calculus (e.g. | 7,143 |
(i.e. or combination and CF semantics Bayesian rules), a | Bayesian or CF combination rules), and a semantics (i.e. | 7,144 |
rational syntax studies scope and languages paper the the those This calculus grounds. on of | This paper studies the rational scope of those languages on the syntax and calculus grounds. | 7,145 |
about One the of Turing of the unorganized idea of was evolutionary computation roots machines. | One of the roots of evolutionary computation was the idea of Turing about unorganized machines. | 7,146 |
holds This observation as ants for as well for fruit flies. | This observation holds for ants as well as for fruit flies. | 7,147 |
compelling effect evidence in a also paper married provides versus unmarried The of (i.e. similar | The paper also provides compelling evidence of a similar effect in married versus unmarried (i.e. | 7,148 |
the the of regimes. A concerns natural two between dynamic question transition the | A natural question concerns the dynamic of the transition between the two regimes. | 7,149 |
This with used factors. uncertainty, certainty by the examines to called paper MYCIN reason quantities | This paper examines the quantities used by MYCIN to reason with uncertainty, called certainty factors. | 7,150 |
shown probabilistic that accommodates is an of number unlimited It this redefinition interpretations. | It is shown that this redefinition accommodates an unlimited number of probabilistic interpretations. | 7,151 |
transformations shown be the These p(EIH)/p(El of are likelihood to ratio monotonic interpretations H). | These interpretations are shown to be monotonic transformations of the likelihood ratio p(EIH)/p(El H). | 7,152 |
assumptions in in the rarely implicit model are applications. It practical true that is emphasized | It is emphasized that assumptions implicit in the model are rarely true in practical applications. | 7,153 |
Methods the suggested. are relaxing assumptions for | Methods for relaxing the assumptions are suggested. | 7,154 |
paper a diagnosis of of model development Bayesian for causal describes This appendicitis. the the | This paper describes the development of a causal Bayesian model for the diagnosis of appendicitis. | 7,155 |
a It axiomatic i.e. basis, well-understood yields | It yields a well-understood axiomatic basis, i.e. | 7,156 |
conditional previous on to work confirmation interpret theory. quantitative independence, | conditional independence, to interpret previous work on quantitative confirmation theory. | 7,157 |
This flexibility requires existing uncertainty than display. more systems | This requires more flexibility than existing uncertainty systems display. | 7,158 |
when tries needs. one to satisfy these | when one tries to satisfy these needs. | 7,159 |
associated true/false These set a and their dependencies. propositions maintain systems of | These systems maintain a set of true/false propositions and their associated dependencies. | 7,160 |
Systems. of reasoning as paper This Maintenance the addresses to it probabilistic applies problem Truth | This paper addresses the problem of probabilistic reasoning as it applies to Truth Maintenance Systems. | 7,161 |
tree-like hierarchical and for formulated inference Strategies are networks Control investigated. probabilistic | Control Strategies for hierarchical tree-like probabilistic inference networks are formulated and investigated. | 7,162 |
properties Various in have use entropy information to its led theory. widespread of relative | Various properties of relative entropy have led to its widespread use in information theory. | 7,163 |
commitments to explanatory formalise Social justificatory patterns. are and used | Social commitments are used to formalise justificatory and explanatory patterns. | 7,164 |
of The combination justification, planation, and commitments . ex- | The combination of ex- planation, justification, and commitments . | 7,165 |
directed Influence probabilities. are diagrams graph a for as representation uncertainties | Influence diagrams are a directed graph representation for uncertainties as probabilities. | 7,166 |
the from of altering hypotheses. the updating-that preclude prevent evidence is, the probabilities | preclude updating-that is, prevent the evidence from altering the probabilities of the hypotheses. | 7,167 |
and a specifying conjunction Each a operator. disjunction calculus negation, defined a is by | Each calculus is defined by specifying a negation, a conjunction and a disjunction operator. | 7,168 |
The i.e. define uncertainty term the set granularity, will | The term set will define the uncertainty granularity, i.e. | 7,169 |
distinction finest uncertainty. quantifications among of level the different of | the finest level of distinction among different quantifications of uncertainty. | 7,170 |
operators. two will granularity between to the limit ability similar This differentiate | This granularity will limit the ability to differentiate between two similar operators. | 7,171 |
formalism problem tool networks as inference used representation. are the Bayesian for space and state | Bayesian inference networks and state space formalism are used as the tool for problem representation. | 7,172 |
permit general computation Pearl's localized this Trees of type sense. in | Trees of this general type permit localized computation in Pearl's sense. | 7,173 |
conditional judgments based of qualitative They are on independence. | They are based on qualitative judgments of conditional independence. | 7,174 |
describe that expert the prove in scheme useful here we will We systems. believe | We believe that the scheme we describe here will prove useful in expert systems. | 7,175 |
demands structure. unrealistic on schemes, the for Bayesian hand, make often other | Bayesian schemes, on the other hand, often make unrealistic demands for structure. | 7,176 |
introduction the a belief functions. section, give In next we to brief | In the next section, we give a brief introduction to belief functions. | 7,177 |
characteristics of the together discussed computational methods the from formulas are These with derived them. | These formulas are discussed together with the computational characteristics of the methods derived from them. | 7,178 |
linear between with These events of constraints the. compute necessary relations probabilities are to | These linear constraints are necessary to compute probabilities of events with relations between the. | 7,179 |
propositional formulas. calculus arbitrarily specified with boolean | arbitrarily specified with propositional calculus boolean formulas. | 7,180 |
uncertain represented be applications can inference systems Expert involve by table. that multidimensional contingency a | Expert systems applications that involve uncertain inference can be represented by a multidimensional contingency table. | 7,181 |
We a present two rigid-body approach segmentation new views. motion from to | We present a new approach to rigid-body motion segmentation from two views. | 7,182 |
Circumscription. Pointwise We a using formalization propose | We propose a formalization using Pointwise Circumscription. | 7,183 |
Projection method Rotational novel presents (RoPS). paper named a Statistics This | This paper presents a novel method named Rotational Projection Statistics (RoPS). | 7,184 |
techniques. to superior exhibited compared Our techniques existing performance proposed | Our proposed techniques exhibited superior performance compared to existing techniques. | 7,185 |
in on expert designing This uncertain environments. making paper focuses support complex, systems decision to | This paper focuses on designing expert systems to support decision making in complex, uncertain environments. | 7,186 |
or of in are belief belief paper, this In updates measures examined. change | In this paper, measures of change in belief or belief updates are examined. | 7,187 |
properties of are In of in belief the spirit Cox, measure change enumerated. for a | In the spirit of Cox, properties for a measure of change in belief are enumerated. | 7,188 |
call between another supports we meta-support. facts supportive relationship fact a this When | When a fact supports another supportive relationship between facts we call this meta-support. | 7,189 |
the This reasoning both facilitates about propositional knowledge. | This facilitates reasoning about both the propositional knowledge. | 7,190 |
(CHO) genome-scale reconstruction a created cell ovary metabolism. chinese We of have hamster network | We have created a genome-scale network reconstruction of chinese hamster ovary (CHO) cell metabolism. | 7,191 |
Preference any inefficient. of food, one kind be such for might circumstances, under | Preference for any one kind of food, under such circumstances, might be inefficient. | 7,192 |
is the to typically which evidence is stored from Moreover, hypothesis. evidence in direction | Moreover, the direction in which evidence is stored is typically from evidence to hypothesis. | 7,193 |
with inference. and inductive dealing -models different to knowledge probabilistic are Two approaches examined | Two different approaches to dealing with probabilistic knowledge are examined -models and inductive inference. | 7,194 |
the The basic appears inductive first be sight very for approach issue different. to at | The basic issue for the inductive approach appears at first sight to be very different. | 7,195 |
be of approach some invoked. induction requires this form Clearly, that | Clearly, this approach requires that some form of induction be invoked. | 7,196 |
Of important manageability is additional course, an concern. | Of course, manageability is an important additional concern. | 7,197 |
inference uncertainty. the of form on strongly representation depend of rules and justification inductive The | The form and justification of inductive inference rules depend strongly on the representation of uncertainty. | 7,198 |
information. incomplete representation, examines paper generic one This namely, | This paper examines one generic representation, namely, incomplete information. | 7,199 |
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