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Bayesian abductive logic programs (2010)
| Content Provider | CiteSeerX |
|---|---|
| Author | Raghavan, Sindhu Mooney, Raymond |
| Description | In this paper, we introduce Bayesian Abductive Logic Programs (BALPs), a new formalism that integrates Bayesian Logic Programs (BLPs) and Abductive Logic Programming (ALP) for abductive reasoning. Like BLPs, BALPs also combine first-order logic and Bayesian networks. However, unlike BLPs that use logical deduction to construct Bayes nets, BALPs employ logical abduction. As a result, BALPs are more suited for solving problems like plan/activity recognition and diagnosis that require abductive reasoning. First, we present the necessary enhancements to BLPs in order to support logical abduction. Next, we apply BALPs to the task of plan recognition and demonstrate its efficacy on two data sets. We also compare the performance of BALPs with several existing approaches for abduction. 1 |
| File Format | |
| Language | English |
| Publisher Date | 2010-01-01 |
| Publisher Institution | In AAAI-2010 Workshop on Statistical Relational AI |
| Access Restriction | Open |
| Subject Keyword | Bayes Net Bayesian Logic Program First-order Logic Bayesian Network Abductive Logic Programming Data Set Logical Abduction Necessary Enhancement Plan Activity Recognition Bayesian Abductive Logic Program Plan Recognition Logical Deduction New Formalism Abductive Reasoning |
| Content Type | Text |
| Resource Type | Article |
