Resolution Based Explanations for Reasoning in the Description Logic
... description logics, we extend our previous work and present an algorithm that generates explanations for unsatisfiability and inconsistency reasoning in the description language . The main advantage of our approach is that it is independent of any specific DL reasoners. ...
... description logics, we extend our previous work and present an algorithm that generates explanations for unsatisfiability and inconsistency reasoning in the description language . The main advantage of our approach is that it is independent of any specific DL reasoners. ...
Two Forms of Dependence in Propositional Logic
... has received much attention recently, is independence (Darwiche 1997) (Lakemeyer 1997) and related structural properties such as relevance (Lakemeyer 1995), or causal independence (Darwiche & Pearl 1994). Revealing independence relations in not only helps understanding better but also is a great ...
... has received much attention recently, is independence (Darwiche 1997) (Lakemeyer 1997) and related structural properties such as relevance (Lakemeyer 1995), or causal independence (Darwiche & Pearl 1994). Revealing independence relations in not only helps understanding better but also is a great ...
Resolve and Expand
... Eliminating variables by resolution as in DP can be lifted from SAT to QBF as well. The result is a bottom-up approach for QBF called q-resolution [10]. The only difference between q-resolution and ordinary resolution is, that in certain cases universally quantified variables can be dropped from the ...
... Eliminating variables by resolution as in DP can be lifted from SAT to QBF as well. The result is a bottom-up approach for QBF called q-resolution [10]. The only difference between q-resolution and ordinary resolution is, that in certain cases universally quantified variables can be dropped from the ...
Ordering attributes for missing values prediction and
... in the network (cutset) and instantiating them. This cutset search is a complex task [2], but once the new structure is created, the propagation can be implemented in a simpler way. In this work the general bayesian conditioning (GBC) [4] is used. It considers that in a data mining prediction work m ...
... in the network (cutset) and instantiating them. This cutset search is a complex task [2], but once the new structure is created, the propagation can be implemented in a simpler way. In this work the general bayesian conditioning (GBC) [4] is used. It considers that in a data mining prediction work m ...
Conditional proof can only be used to deduce a conditional claim
... dependent on the assumption made. You cannot take that formula and use it on any line that is not within the conditional proof lines. You can construct more than one conditional proof in a deduction, but, when you do so, they either need to be (1) nested or (2) separate entirely. We cannot have a ca ...
... dependent on the assumption made. You cannot take that formula and use it on any line that is not within the conditional proof lines. You can construct more than one conditional proof in a deduction, but, when you do so, they either need to be (1) nested or (2) separate entirely. We cannot have a ca ...
The joint distribution of the time to ruin and the number of claims
... as representing the probability that ruin occurs on the (n + 1)th claim and in the interval (t, t + dt). The surplus falls below 0 on the (n + 1)th claim and in the interval (t, t+dt) it there are n claims up to time t of total amount u + ct − x, so that the surplus is x at time t, and if a claim ex ...
... as representing the probability that ruin occurs on the (n + 1)th claim and in the interval (t, t + dt). The surplus falls below 0 on the (n + 1)th claim and in the interval (t, t+dt) it there are n claims up to time t of total amount u + ct − x, so that the surplus is x at time t, and if a claim ex ...
Possibilistic conditional independence: A similarity
... operational criterion for identifying such relations from summarized information, as uncertainty distributions are. We will not review here the various techniques used in probability to detect such relations, the Z2 test and its variations being the most classical ones. Our interest lies in defining ...
... operational criterion for identifying such relations from summarized information, as uncertainty distributions are. We will not review here the various techniques used in probability to detect such relations, the Z2 test and its variations being the most classical ones. Our interest lies in defining ...
Mixed Recursion: Sec. 8.4
... Exercise 7. To help him finish his final year of college, Sam took out a loan of $5,000. At the end of the first year after he graduated, there was a $4,500 balance, and at the end of the second year, $3,950 remained. The amount of money left at the end of n years can be modeled by the mixed recurre ...
... Exercise 7. To help him finish his final year of college, Sam took out a loan of $5,000. At the end of the first year after he graduated, there was a $4,500 balance, and at the end of the second year, $3,950 remained. The amount of money left at the end of n years can be modeled by the mixed recurre ...
Mathematical Logic 2016 Lecture 4: Normal forms
... Modify the encoding such that it works without the assumptions at step 1 Hint: Download sat solver $wget http://fmv.jku.at/limboole/limboole1.1.tar.gz look for function tseitin in file limboole.c cbna Mathematical Logic 2016 Instructor: Ashutosh Gupta TIFR, India ...
... Modify the encoding such that it works without the assumptions at step 1 Hint: Download sat solver $wget http://fmv.jku.at/limboole/limboole1.1.tar.gz look for function tseitin in file limboole.c cbna Mathematical Logic 2016 Instructor: Ashutosh Gupta TIFR, India ...
Markov logic networks | SpringerLink
... constructed from atomic formulas using logical connectives and quantifiers. If F1 and F2 are formulas, the following are also formulas: ¬F1 (negation), which is true iff F1 is false; F1 ∧ F2 (conjunction), which is true iff both F1 and F2 are true; F1 ∨ F2 (disjunction), which is true iff F1 or F2 i ...
... constructed from atomic formulas using logical connectives and quantifiers. If F1 and F2 are formulas, the following are also formulas: ¬F1 (negation), which is true iff F1 is false; F1 ∧ F2 (conjunction), which is true iff both F1 and F2 are true; F1 ∨ F2 (disjunction), which is true iff F1 or F2 i ...
C Operator Problem Solving
... The formula for converting centigrade temperatures to Fahrenhit is as shown below. Write a program that asks the user to enter a temperature reading in centigrade and then prints the equivalent Fahrenhit value. F = 32 + ...
... The formula for converting centigrade temperatures to Fahrenhit is as shown below. Write a program that asks the user to enter a temperature reading in centigrade and then prints the equivalent Fahrenhit value. F = 32 + ...
Lesson 7 Solutions - Full
... Notice that each row of beads contains one more bead than the row below it. The exercises below involve counting the number of beads in the design. 1. Count the number of beads in Rows 1 – 10. SOLUTION: There are j beads in row j. Summing for j = 1, 2, 3, …, 10, we find that the total number of bead ...
... Notice that each row of beads contains one more bead than the row below it. The exercises below involve counting the number of beads in the design. 1. Count the number of beads in Rows 1 – 10. SOLUTION: There are j beads in row j. Summing for j = 1, 2, 3, …, 10, we find that the total number of bead ...
Implicit Learning of Common Sense for Reasoning
... (possibly exponential-size) KB itself will appear only in our analysis of a combined system for learning and reasoning. Technically, our contribution is that we exhibit computationally efficient algorithms for reasoning under PACSemantics using both explicitly given rules and rules that are learned ...
... (possibly exponential-size) KB itself will appear only in our analysis of a combined system for learning and reasoning. Technically, our contribution is that we exhibit computationally efficient algorithms for reasoning under PACSemantics using both explicitly given rules and rules that are learned ...
Solving Bayesian Networks by Weighted Model Counting
... problems can be exactly solved in practice by translation to model-counting and the application of a general modelcounting algorithm. This paper provides initial evidence that the answer is affirmative: such a translation approach can indeed be effective for interesting classes of hard problems that ...
... problems can be exactly solved in practice by translation to model-counting and the application of a general modelcounting algorithm. This paper provides initial evidence that the answer is affirmative: such a translation approach can indeed be effective for interesting classes of hard problems that ...
Mining Incomplete Data with Many Missing Attribute Values
... represents, e.g., a refusal to answer a question. For example, patients suspected of having flu may refuse to tell the value of the attribute Eye color since they may consider it irrelevant. For data mining from data sets affected by such missing attribute values we replace a “do not care” condition ...
... represents, e.g., a refusal to answer a question. For example, patients suspected of having flu may refuse to tell the value of the attribute Eye color since they may consider it irrelevant. For data mining from data sets affected by such missing attribute values we replace a “do not care” condition ...
Inferential Statistics III
... Probability statistics are the most common way to evaluate relationships, but they are being criticized for suggesting misleading results. (Click here for a summary of the arguments.) We normally use p values to accept or reject null hypotheses. But the actual meaning is more subtle: – Formally, a p ...
... Probability statistics are the most common way to evaluate relationships, but they are being criticized for suggesting misleading results. (Click here for a summary of the arguments.) We normally use p values to accept or reject null hypotheses. But the actual meaning is more subtle: – Formally, a p ...
7. Propositional Logic Rational Thinking, Logic, Resolution
... Before a system that is capable of learning, thinking, planning, explaining, . . . can be built, one must find a way to express knowledge. We need a precise, declarative language. Declarative: System believes P if and only if (iff) it considers P to be true (one cannot believe P without an idea of w ...
... Before a system that is capable of learning, thinking, planning, explaining, . . . can be built, one must find a way to express knowledge. We need a precise, declarative language. Declarative: System believes P if and only if (iff) it considers P to be true (one cannot believe P without an idea of w ...
Formula-Based Probabilistic Inference - Washington
... A more serious problem is the lack of efficient inference procedures for probabilistic logic. This contrasts with the large literature on inference for graphical models, which always specify unique and consistent distributions (Pearl, 1988). However, the representational flexibility and compactness ...
... A more serious problem is the lack of efficient inference procedures for probabilistic logic. This contrasts with the large literature on inference for graphical models, which always specify unique and consistent distributions (Pearl, 1988). However, the representational flexibility and compactness ...
Artificial Intelligence
... + 100000*G + 10000*E + 1000*R + 100*A+ 10*L + D = 100000*R + 10000*O + 1000*B + 100*E+ 10*R + T ...
... + 100000*G + 10000*E + 1000*R + 100*A+ 10*L + D = 100000*R + 10000*O + 1000*B + 100*E+ 10*R + T ...
PDF
... food detention. Considering the interaction of dissimilarity to FDI and overlap between the two groups, fertilizer consumption is the ...
... food detention. Considering the interaction of dissimilarity to FDI and overlap between the two groups, fertilizer consumption is the ...
Ontology of Actions
... the endpoint of one event may be the starting-point of another one, but two events may not have more than one point (an endpoint) in common. For example, one event recognizer may identify periods of time during which a helicopter first starts its engine, then takes off, flies, lands at another point ...
... the endpoint of one event may be the starting-point of another one, but two events may not have more than one point (an endpoint) in common. For example, one event recognizer may identify periods of time during which a helicopter first starts its engine, then takes off, flies, lands at another point ...
Round to - Ohio State Computer Science and Engineering
... Sums the number of items in a range that meet a specific criteria =SUMIF(criteria_range, criteria,[sum_range]) Averages the number of items in a range that meet a specific criteria =AVERAGEIF(criteria_range, criteria,[average_range]) • Criteria_Range: A continuous range • Criteria: Determines what c ...
... Sums the number of items in a range that meet a specific criteria =SUMIF(criteria_range, criteria,[sum_range]) Averages the number of items in a range that meet a specific criteria =AVERAGEIF(criteria_range, criteria,[average_range]) • Criteria_Range: A continuous range • Criteria: Determines what c ...
Revised October 2009
... and logic. Recent developments include efforts to extend the syntax of programs as well as to deal more directly with variables in a full, first-order context. In several cases, assumptions such as standard names (SNA) are being relaxed and issues involving programming in open domains are being addr ...
... and logic. Recent developments include efforts to extend the syntax of programs as well as to deal more directly with variables in a full, first-order context. In several cases, assumptions such as standard names (SNA) are being relaxed and issues involving programming in open domains are being addr ...
Simple concepts
... that contains simple concepts, so by any complex concept. Consider the concept D from 17: x [0= [0Card y [0Div x y] 02]] The set of pairs, where x is divisible by y is infinite. So is the set of those
numbers that have just two divisors. Thus the difficulty A. is independent of the
difficul ...
... that contains simple concepts, so by any complex concept. Consider the concept D from 17: x [0= [0Card y [0Div x y] 02]] The set of pairs
Quantitatively Evaluating Formula-Variable Relevance by
... in which ϕ is true. Mod(ϕ) denotes the set of models of ϕ with respect to the variables in the set P S. We say formula φ entails formula ψ, denoted by φ |= ψ, if Mod(φ) ⊆ Mod(ψ). We say φ and ψ are logically equivalent, denoted by φ ≡ ψ, if Mod(φ) = Mod(ψ). Variable forgetting on propositional logic ...
... in which ϕ is true. Mod(ϕ) denotes the set of models of ϕ with respect to the variables in the set P S. We say formula φ entails formula ψ, denoted by φ |= ψ, if Mod(φ) ⊆ Mod(ψ). We say φ and ψ are logically equivalent, denoted by φ ≡ ψ, if Mod(φ) = Mod(ψ). Variable forgetting on propositional logic ...
Granular computing
Granular computing (GrC) is an emerging computing paradigm of information processing. It concerns the processing of complex information entities called information granules, which arise in the process of data abstraction and derivation of knowledge from information or data. Generally speaking, information granules are collections of entities that usually originate at the numeric level and are arranged together due to their similarity, functional or physical adjacency, indistinguishability, coherency, or the like.At present, granular computing is more a theoretical perspective than a coherent set of methods or principles. As a theoretical perspective, it encourages an approach to data that recognizes and exploits the knowledge present in data at various levels of resolution or scales. In this sense, it encompasses all methods which provide flexibility and adaptability in the resolution at which knowledge or information is extracted and represented.