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The interaction of representation and reasoning
Author(s) -
Alan Bundy
Publication year - 2013
Publication title -
proceedings of the royal society a mathematical physical and engineering sciences
Language(s) - English
Resource type - Journals
eISSN - 1471-2946
pISSN - 1364-5021
DOI - 10.1098/rspa.2013.0194
Subject(s) - computer science , knowledge representation and reasoning , automated reasoning , inference , reasoning system , opportunistic reasoning , representation (politics) , model based reasoning , analytic reasoning , artificial intelligence , deductive reasoning , process (computing) , automation , task (project management) , qualitative reasoning , domain (mathematical analysis) , human–computer interaction , programming language , mathematics , mechanical engineering , mathematical analysis , management , politics , political science , law , economics , engineering
Automated reasoning is an enabling technology for many applications of informatics. These applications include verifying that a computer program meets its specification; enabling a robot to form a plan to achieve a task and answering questions by combining information from diverse sources, e.g. on the Internet, etc. How is automated reasoning possible? Firstly, knowledge of a domain must be stored in a computer, usually in the form of logical formulae. This knowledge might, for instance, have been entered manually, retrieved from the Internet or perceived in the environment via sensors, such as cameras. Secondly, rules of inference are applied to old knowledge to derive new knowledge. Automated reasoning techniques have been adapted from logic, a branch of mathematics that was originally designed to formalize the reasoning of humans, especially mathematicians. My special interest is in the way that representation and reasoning interact. Successful reasoning is dependent on appropriate representation of both knowledge and successful methods of reasoning. Failures of reasoning can suggest changes of representation. This process of representational change can also be automated. We will illustrate the automation of representational change by drawing on recent work in my research group.

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