Abstract
In order for an agent to achieve its objectives, make sound decisions, communicate and collaborate with others effectively it must have high quality representations. Representations can encapsulate objects, situations, experiences, decisions and behavior just to name a few. Our interest is in designing high quality representations, therefore it makes sense to ask of any representation; what does it represent; why is it represented; how is it represented; and importantly how well is it represented. This paper identifies the need to develop a better understanding of the grounding process as key to answering these important questions. The lack of a comprehensive understanding of grounding is a major obstacle in the quest to develop genuinely intelligent systems that can make their own representations as they seek to achieve their objectives. We develop an innovative framework which provides a powerful tool for describing, dissecting and inspecting grounding capabilities with the necessary flexibility to conduct meaningful and insightful analysis and evaluation. The framework is based on a set of clearly articulated principles and has three main applications. First, it can be used at both theoretical and practical levels to analyze grounding capabilities of a single system and to evaluate its performance. Second, it can be used to conduct comparative analysis and evaluation of grounding capabilities across a set of systems. Third, it offers a practical guide to assist the design and construction of high performance systems with effective grounding capabilities.
Original language | English |
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Pages (from-to) | 272-296 |
Journal | Autonomous Agents and Multi-Agent Systems |
Volume | 19 |
Issue number | 3 |
DOIs | |
Publication status | Published - 2009 |
Subject classification (UKÄ)
- General Language Studies and Linguistics
- Learning
Free keywords
- Artificial intelligence
- Perception
- Grounding
- Knowledge representation
- Cognitive robotics