Enhancing Intelligent Agents with Information Retrieval Techniques

Abstract

Learning is an integral part of an intelligent agent's problem-solving ability. Most research works on learning assume that information are provided in a complete and well-structured manner and/or when rules are clearly specified, therefore have difficulties in handling cases with incomplete and unstructured data. This paper presents a novel approach to deal with this difficulty. It uses information retrieval techniques to enhance an agent's reasoning and problem-solving ability when only incomplete and unstructured information are available. Preliminary experimental results show that the integration of information retrieval can effectively help an agent to analyze the problem before solving it.