Bayesian Knowledge Bases
From Distributed Information and Intelligence Analysis Group
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A Bayesian knowledge-base is a knowledge representation system that has a similar structure as a Bayesian network. It represents knowledge by an “if-then” structure and represents uncertainty by probability theory. BKBs subsume BNs and are advantageous to BNs because BKBs are robust to knowledge incompleteness and cyclic information, while still preserving a probabilistically sound representation of uncertainty. We now extend BKBs to represent both time and interaction since time is the key component of a dynamic world. We target to provide a comprehensive model that can describe the interactions of knowledge in the world, as well as reason through them. | A Bayesian knowledge-base is a knowledge representation system that has a similar structure as a Bayesian network. It represents knowledge by an “if-then” structure and represents uncertainty by probability theory. BKBs subsume BNs and are advantageous to BNs because BKBs are robust to knowledge incompleteness and cyclic information, while still preserving a probabilistically sound representation of uncertainty. We now extend BKBs to represent both time and interaction since time is the key component of a dynamic world. We target to provide a comprehensive model that can describe the interactions of knowledge in the world, as well as reason through them. | ||
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| + | * [[Culturally Infused Social Network Analysis]] | ||
| + | * [[Adversary Intent Inferencing|Adversary Intent Inferencing]] | ||
| + | * [[CyberCAFE|CyberCAFE]] | ||
| + | * [[Surgical Intent|Surgical Intent]] | ||
| + | * [[MURI|MURI]] | ||
| + | * [[Knowledge Engineering under Time and Uncertainty]] | ||
Revision as of 23:58, 25 June 2009
A Bayesian knowledge-base is a knowledge representation system that has a similar structure as a Bayesian network. It represents knowledge by an “if-then” structure and represents uncertainty by probability theory. BKBs subsume BNs and are advantageous to BNs because BKBs are robust to knowledge incompleteness and cyclic information, while still preserving a probabilistically sound representation of uncertainty. We now extend BKBs to represent both time and interaction since time is the key component of a dynamic world. We target to provide a comprehensive model that can describe the interactions of knowledge in the world, as well as reason through them.
