{ Logic in Artificial Intelligence By Jeremy Wright Mathematical Logic April 10 th, 2012.

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Presentation transcript:

{ Logic in Artificial Intelligence By Jeremy Wright Mathematical Logic April 10 th, 2012

 “AI is a subfield of Computer Science devoted to developing programs that display behavior that can be characterized as intelligent.  Desire to have intelligent, independent entities  Currently limited to more narrow applications  Planning  Speech-to-speech translation  etc Background

 Theoretical computation based in logic  Logical Programming Influences in Computation

 Analysis  Basis for Knowledge Representation  Programming Language Uses for Logic in AI

 Scientific Theories Represent Compartmentalized Knowledge   Common-sense reasoning is required for solving problems in the common- sense world   Informal metatheory of any scientific theory has a common- sense informatic character Common Sense vs. Scientific Theories

  A machine may use no logical sentences   Computer programs that use sentences in machine memory to represent their beliefs but use other rules than ordinary logical inference to reach conclusions   Using first order logic and also logical deduction   Representing general facts about the world as logical sentences Four Levels of Logic in AI

  Entities of interest are known only partially, and the information about entities and their relations that may be relevant to achieving goals cannot be permanently separated from irrelevant information.   The formalism has to be epistemologically adequate   formalism must be capable of representing the information that is actually available, not merely capable of representing actual complete states of affairs Reaching Fourth Stage

 Monotonic Logic states that if one can prove p from A and A is contained in B, then one can prove p from B  Follows from deductive means but some human reasoning is not monotonic.  Example: If one is hired to build a bird age, one assumes that there should be a top on it but it does not follow from monotonic reasoning in some cases  Probabilistic Reasoning Nonmonotonic Reasoning

 AI would have reason about what it can and cannot do  If one has two choices, B and C, an AI should be able to decide which of the two it should use to either accomplish a goal, say A, or choose based on provided criteria Practical Reason and Free Will

 AI should have ability to reason about its knowledge and that of other AI and people  Make judgments on appropriate courses of action  Example: designing a trip via air and picking intermediate stops along the way  Knowledge of airline schedules, locations, distances, etc. Knowledge and Belief

 Stanford Encyclopedia of Philosophy  “  “Artificial Intelligence, Logic and Formalizing Common Sense” by John McCarthy, Stanford University Resources