Learning to Reason

We introduce a new framework for the study of reasoning. The Learning (in order) to Reason approach developed here views learning as an integral part of the inference process, and suggests that learning and reasoning should be studied together. The Learning to Reason framework combines the interfaces to the world used by known learning models with the reasoning task and a performance criterion suitable for it. In this framework, the intelligent agent is given access to its favorite learning interface, and is also given a grace period in which it can interact with this interface and construct a representation KB of the world W. The reasoning performance is measured only after this period, when the agent is presented with queries from some query language, relevant to the world, and has to answer whether W implies . The approach is meant to overcome the main computational difficulties in the traditional treatment of reasoning which stem from its separation from the "world". Sinc...

• Type: Conference
• Year: 1994
• Where: AAAI
• Authors: Roni Khardon, Dan Roth
• Keywords: AAAI 1994, Intelligent Agents, Known Learning Models, Reasoning, Reasoning Performance