PPT-Logical Inference 3 resolution

Chapter 9 Some material adopted from notes by Andreas GeyerSchulz Chuck Dyer and Mary Getoor 943 Resolution Resolution is a sound and complete inference procedure for unrestricted FOL. Lecturer: Xinming (Simon) Ou. CIS 505: Programming Languages. Fall 2010. Kansas State University. 1. What we have covered so far:. Imperative paradigm. Computes effects. Functional paradigm. Computes values. Presented By: Ms. . Seawright. What does it mean to make an inference?. Make an inference.. Use what you already know.. The inference equation. WHAT I READ. Use quotes from the text and not page number for future references. and First-Order Logic. Inference rules. Logical inference. creates new sentences that logically follow from a set of sentences (KB). An inference rule is . sound. if every sentence X it produces when operating on a KB logically follows from the KB. CS482, CS682, MW 1 – 2:15, SEM 201, MS 227. Prerequisites: 302, 365. Instructor: . Sushil. Louis, . sushil@cse.unr.edu. , . http://www.cse.unr.edu/~. sushil. Logic. Logical Agents. Truth . tables you know. Peter M. Maurer. Propositions. A proposition is a declarative sentence that can be either true or false. Earth is a planet – True. The Moon is made of green cheese – False. There is life on Mars – We don’t know yet, but either there is or there isn’t. Protocols for Coreference Resolution. . . Kai-Wei Chang, Rajhans Samdani. , . Alla Rozovskaya, Nick Rizzolo, Mark Sammons. , and Dan Roth. . do not follow textbook closely. 2. M(alpha)=M(beta). 3. Model-checking. contradiction or refutation. alpha is valid . iff. ~alpha is . unsatisfiable. 4. KB&~. a. False. False. False. False. False. and First-Order Logic. Inference rules. Logical inference. creates new sentences that logically follow from a set of sentences (KB). An inference rule is . sound. if every sentence X it produces when operating on a KB logically follows from the KB. Session 6. Course : T0273 – EXPERT SYSTEMS. Year : 2014. Learning Outcomes. LO 2 : Describe the characteristics of Expert Systems. After taking this course, students should be expected to explain and use the Method of inference.. Bart Selman. selman@cs.cornell.edu. Module: Knowledge, Reasoning, and Planning. Logical Agents. Model . Theoretic Semantics. Entailment . and Proof Theory. R&N: Chapter 7. Logical agents:. . . Bart Selman. selman@cs.cornell.edu. Module: Knowledge, Reasoning, and Planning. Part 1. Logical Agents. R&N: Chapter 7. A Model-Based Agent. Requires: Knowledge and Reasoning. Knowledge and Reasoning . Sriraam Natarajan. Dept of . Computer Science, . University . of . Wisconsin-Madison. Take-Away Message . Inference. in SRL Models is . very hard. !!!!. This talk – Presents . 3 different yet related. Chapter 9. Some material adopted from notes by Andreas Geyer-Schulz,, Chuck Dyer, and Mary . Getoor. Overview. A: Model checking for propositional logic. Rule based reasoning in first-order logic. Inference rules and generalized modes ponens. Adapted from Patrick J. Hurley, . A Concise Introduction to Logic. (Belmont: Thomson Wadsworth, 2008).. Predicate Logic. Before I go on to explain quantifiers, first let me address different ways of symbolizing statements. Previously, we used one letter to symbolize one statement. But there is another way to symbolize certain kinds of statements that are relevant to quantifiers. We can also symbolize statements by symbolizing the predicate and subject separately. .