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327 results on '"KORB, KEVIN B."'

101. Loopy Belief Propagation

Author

Webb, Geoffrey I., primary, Sammut, Claude, additional, Perlich, Claudia, additional, Horváth, Tamás, additional, Wrobel, Stefan, additional, Korb, Kevin B., additional, Noble, William Stafford, additional, Leslie, Christina, additional, Lagoudakis, Michail G., additional, Quadrianto, Novi, additional, Buntine, Wray L., additional, Getoor, Lise, additional, Namata, Galileo, additional, Han, Xin Jin, Jiawei, additional, Ting, Jo-Anne, additional, Vijayakumar, Sethu, additional, Schaal, Stefan, additional, and Raedt, Luc De, additional

Published
2011
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102. Learning Bayesian Networks

Author

Webb, Geoffrey I., primary, Sammut, Claude, additional, Perlich, Claudia, additional, Horváth, Tamás, additional, Wrobel, Stefan, additional, Korb, Kevin B., additional, Noble, William Stafford, additional, Leslie, Christina, additional, Lagoudakis, Michail G., additional, Quadrianto, Novi, additional, Buntine, Wray L., additional, Getoor, Lise, additional, Namata, Galileo, additional, Han, Xin Jin, Jiawei, additional, Ting, Jo-Anne, additional, Vijayakumar, Sethu, additional, Schaal, Stefan, additional, and Raedt, Luc De, additional

Published
2011
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103. Leave-One-Out Error

Author

Webb, Geoffrey I., primary, Sammut, Claude, additional, Perlich, Claudia, additional, Horváth, Tamás, additional, Wrobel, Stefan, additional, Korb, Kevin B., additional, Noble, William Stafford, additional, Leslie, Christina, additional, Lagoudakis, Michail G., additional, Quadrianto, Novi, additional, Buntine, Wray L., additional, Getoor, Lise, additional, Namata, Galileo, additional, Han, Xin Jin, Jiawei, additional, Ting, Jo-Anne, additional, Vijayakumar, Sethu, additional, Schaal, Stefan, additional, and Raedt, Luc De, additional

Published
2011
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104. Latent Class Model

Author

Webb, Geoffrey I., primary, Sammut, Claude, additional, Perlich, Claudia, additional, Horváth, Tamás, additional, Wrobel, Stefan, additional, Korb, Kevin B., additional, Noble, William Stafford, additional, Leslie, Christina, additional, Lagoudakis, Michail G., additional, Quadrianto, Novi, additional, Buntine, Wray L., additional, Getoor, Lise, additional, Namata, Galileo, additional, Han, Xin Jin, Jiawei, additional, Ting, Jo-Anne, additional, Vijayakumar, Sethu, additional, Schaal, Stefan, additional, and Raedt, Luc De, additional

Published
2011
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105. Local Distance Metric Adaptation

Author

Webb, Geoffrey I., primary, Sammut, Claude, additional, Perlich, Claudia, additional, Horváth, Tamás, additional, Wrobel, Stefan, additional, Korb, Kevin B., additional, Noble, William Stafford, additional, Leslie, Christina, additional, Lagoudakis, Michail G., additional, Quadrianto, Novi, additional, Buntine, Wray L., additional, Getoor, Lise, additional, Namata, Galileo, additional, Han, Xin Jin, Jiawei, additional, Ting, Jo-Anne, additional, Vijayakumar, Sethu, additional, Schaal, Stefan, additional, and Raedt, Luc De, additional

Published
2011
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107. BARD: A Structured Technique for Group Elicitation of Bayesian Networks to Support Analytic Reasoning.

Author

Nyberg, Erik P., Nicholson, Ann E., Korb, Kevin B., Wybrow, Michael, Zukerman, Ingrid, Mascaro, Steven, Thakur, Shreshth, Oshni Alvandi, Abraham, Riley, Jeff, Pearson, Ross, Morris, Shane, Herrmann, Matthieu, Azad, A.K.M., Bolger, Fergus, Hahn, Ulrike, and Lagnado, David

Subjects
BAYESIAN analysis, ELICITATION technique, ARTIFICIAL intelligence, DECISION making, STATISTICAL decision making
Abstract

In many complex, real‐world situations, problem solving and decision making require effective reasoning about causation and uncertainty. However, human reasoning in these cases is prone to confusion and error. Bayesian networks (BNs) are an artificial intelligence technology that models uncertain situations, supporting better probabilistic and causal reasoning and decision making. However, to date, BN methodologies and software require (but do not include) substantial upfront training, do not provide much guidance on either the model building process or on using the model for reasoning and reporting, and provide no support for building BNs collaboratively. Here, we contribute a detailed description and motivation for our new methodology and application, Bayesian ARgumentation via Delphi (BARD). BARD utilizes BNs and addresses these shortcomings by integrating (1) short, high‐quality e‐courses, tips, and help on demand; (2) a stepwise, iterative, and incremental BN construction process; (3) report templates and an automated explanation tool; and (4) a multiuser web‐based software platform and Delphi‐style social processes. The result is an end‐to‐end online platform, with associated online training, for groups without prior BN expertise to understand and analyze a problem, build a model of its underlying probabilistic causal structure, validate and reason with the causal model, and (optionally) use it to produce a written analytic report. Initial experiments demonstrate that, for suitable problems, BARD aids in reasoning and reporting. Comparing their effect sizes also suggests BARD's BN‐building and collaboration combine beneficially and cumulatively. [ABSTRACT FROM AUTHOR]

Published
2022
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125. Causation and Universals

Author

Korb, Kevin B.

Subjects
Causation and Universals (Book) -- Book reviews, Books -- Book reviews, Philosophy and religion
Published
1991

126. The essential roles of emotion in cognitive architecture

Author

Korb, Kevin B. and Nicholson, Ann E.

Subjects
Emotions -- Research, Cognition -- Research, Psychology and mental health
Abstract

Rolls's presentation of emotion as integral to cognition is a welcome counter to a long tradition of treating them as antagonists. His eduction of experimental evidence in support of this view is impressive. However, we find his excursion into the philosophy of consciousness less successful. Rolls gives syntactical manipulation the central role in consciousness (in stark contrast to Searle, for whom 'mere' syntax inevitably falls short of consciousness), and leaves us wondering about the roles left for emotion after all.

Published
2000

130. Improbable Creativity

Author

Dorin, Alan and Korb, Kevin B

Subjects
Creativity, representation, mechanism, complexity, novelty
Abstract

We begin with a number of basic facts about creativity and a brief history of the idea. These provide criteria that any definition of the term should meet and help guide us to a new definition of creativity. This definition is independent of cultural appropriateness or the perceived value of creative objects, ideas which have encumbered previous investigations. We briefly defend our definition against some plausible objections and then explore the ways in which this new definition differs from alternative views, by improving upon them.

Published
2009
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138. Actual causation by probabilistic active paths (Supplement)

Author

Twardy, Charles R., Korb, Kevin B., Twardy, Charles R., and Korb, Kevin B.

Abstract

This online supplement contains peer-reviewed material that would not fit in the PSA 2010 Proceedings article, Twardy and Korb (2011). That article presents a probabilistic extension of active-path analyses of actual causation. The extension uses “soft” interventions (Korb et al., 2004) as the analog of resetting path variables to their actual value. Soft interventions allow the “actual value” to be a probability distribution. The resulting account can handle at least as wide a range of examples as the original accounts, without assuming determinism.

Published
2010

139. Improbable Creativity

Author

Alan Dorin and Kevin B Korb, Dorin, Alan, Korb, Kevin B, Alan Dorin and Kevin B Korb, Dorin, Alan, and Korb, Kevin B

Abstract

We begin with a number of basic facts about creativity and a brief history of the idea. These provide criteria that any definition of the term should meet and help guide us to a new definition of creativity. This definition is independent of cultural appropriateness or the perceived value of creative objects, ideas which have encumbered previous investigations. We briefly defend our definition against some plausible objections and then explore the ways in which this new definition differs from alternative views, by improving upon them.

Published
2009
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141. Epidemiological data mining of cardiovascular Bayesian networks

Author

Twardy, Charles R; Clayton School of Information Technology, Monash University, Nicholson, Ann E; Clayton School of Information Technology, Monash University, Korb, Kevin B; Clayton School of Information Technology, Monash University, McNeil, John; Department of Epidemiology & Preventive Medicine, Monash University, Twardy, Charles R; Clayton School of Information Technology, Monash University, Nicholson, Ann E; Clayton School of Information Technology, Monash University, Korb, Kevin B; Clayton School of Information Technology, Monash University, and McNeil, John; Department of Epidemiology & Preventive Medicine, Monash University

Abstract

Although BNs have been used successfully for many medical diagnosis problems, there have been few applications to epidemiological data where data mining methods play a significant role. In this paper, we look at the application of BNs to epidemiological data, specifically assessment of risk for coronary heart disease (CHD). We build the BNs: (1) by knowledge engineering BNs from two epidemiological models of CHD in the literature; (2) by applying a causal BN learner. We evaluate these BNs using cross-validation. We compared performance in predicting CHD events over 10 years, measuring area under the ROC curve and Bayesian information reward. The knowledge engineered BNs performed as well as logistic regression, while being easier to interpret. These BNs will serve as the baseline in future efforts to extend BN technology to better handle epidemiological data, specifically to model CHD.

Published
2006

142. Token causation by probabilistic active paths

Author

Twardy, Charles R., Korb, Kevin B., Oppy, Graham, Handfield, Toby, Twardy, Charles R., Korb, Kevin B., Oppy, Graham, and Handfield, Toby

Abstract

We present a probabilistic extension to active path analyses of token causation (Halpern & Pearl 2001, forthcoming; Hitchcock 2001). The extension uses the generalized notion of intervention presented in (Korb et al. 2004): we allow an intervention to set any probability distribution over the intervention variables, not just a single value. The resulting account can handle a wide range of examples. We do not claim the account is complete --- only that it fills an obvious gap in previous active-path approaches. It still succumbs to recent counterexamples by Hiddleston (2005), because it does not explicitly consider causal processes. We claim three benefits: a detailed comparison of three active-path approaches, a probabilistic extension for each, and an algorithmic formulation.

Published
2005

145. An Evolutionary Benefit from Misperception in Foraging Behaviour.

Author

Carbonell, Jaime G., Siekmann, Jörg, Randall, Marcus, Abbass, Hussein A., Wiles, Janet, Brumley, Lachlan, Korb, Kevin B., and Kopp, Carlo

Abstract

Misperception is a common cause of error for individuals and organisations. Conventional wisdom suggests that its effects are detrimental to the misperceiver or its society as a whole. However, in some circumstances misperception can provide a benefit either by diversifying the behaviour of a population or by discouraging behaviour that has a negative impact on the population. In such cases adaptive pressures will drive the population to evolve a probability of misperception that is optimal for that environment. We explore this hypothesis using an evolutionary artificial life simulation. [ABSTRACT FROM AUTHOR]

Published
2007
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146. Building Virtual Ecosystems from Artificial Chemistry.

Author

Carbonell, Jaime G., Siekmann, Jörg, Almeida e Costa, Fernando, Rocha, Luis Mateus, Costa, Ernesto, Harvey, Inman, Coutinho, António, Dorin, Alan, and Korb, Kevin B.

Abstract

This paper adopts an interdisciplinary view of the significant elements of ecosystems and the methods by which these might be simulated to explore theoretical issues of relevance to Artificial Life and Ecology. Artificial Life has largely been concerned with evolutionary ecosystems of agents in trivial environments. Ecology commonly produces models of specific habitats and organism populations unsuited to general exploration of theoretical issues. We propose that limitations of the simulations in these disciplines can be overcome by simulating ecosystems from the level of artificial chemistry. We demonstrate the approach's feasibility by describing several virtual organisms represented at this level. The organisms automatically adopt trophic levels, generate energy from chemical bonds and transform material elements in the process. Virtual organisms may interact with one another and their abiotic environment using the same chemistry. Biosynthesis and decay may also be simulated through this mechanism. [ABSTRACT FROM AUTHOR]

Published
2007
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147. An Information-Theoretic Causal Power Theory.

Author

Zhang, Shichao, Jarvis, Ray, Hope, Lucas R., and Korb, Kevin B.

Abstract

A metric of causal power can assist in developing and using causal Bayesian networks. We introduce a metric based upon information theory. We show that it generalizes prior metrics restricted to linear and noisy-or models, while providing a metric appropriate to the full representational power of Bayesian nets. [ABSTRACT FROM AUTHOR]

Published
2005
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