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The interaction of representation and reasoning.
1School of Informatics , University of Edinburgh , Edinburgh EH8 9AB, UK.
Proceedings. Mathematical, Physical, and Engineering Sciences
|September 25, 2013
Summary
Automated reasoning uses logic to derive new knowledge from stored information for informatics applications. Research explores how changing knowledge representation can improve reasoning processes.
Area of Science:
- Computer Science
- Artificial Intelligence
- Mathematical Logic
Background:
- Automated reasoning is crucial for informatics applications like program verification, robotics, and question answering.
- It relies on storing domain knowledge as logical formulae and applying inference rules to derive new knowledge.
Approach:
- This work adapts techniques from mathematical logic to formalize reasoning processes.
- The research focuses on the interaction between knowledge representation and reasoning methods.
- It investigates the automation of representational change to enhance reasoning capabilities.
Key Points:
- Knowledge representation significantly impacts reasoning success.
- Reasoning failures can indicate a need for representational adjustments.
- Automating representational change is explored as a method to improve automated reasoning.
Conclusions:
- Automated reasoning is a foundational technology in computer science and AI.
- The interplay between representation and reasoning is key to developing more effective automated systems.
- Further research into automated representational change promises to advance the field.
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