在二十ㄧ世紀的今日，機器人在日常生活中所扮演的角色越來越多樣化，從工業上重複單一動作的機械手臂，到商業上極具商業價值的多功能機械寵物，各種功能的機器人正被開發出來。在開發一個機器人系統的生命週期中，對研發人員而言，常會遇到一個設計概念經常被反覆使用的情形，雖然相同的設計概念可以被應用在其它機器人，但對一位資淺的研發人員來說，要重複運用這樣的概念並不容易。

有鑑於此，本研究開發出「推薦代理人系統」，目的是希望能讓所保存的設計知識能有效的被運用。推薦代理人系統以「知識本體」作為內部知識文件架構，透過「主題地圖」呈現知識，研發人員可根據設計理念向推薦代理人提出「概念式搜尋」，代理人會根據需求給予適當推薦結果，可分為「知識脈絡」(Knowledge Vein)與「主題導覽」(Topic Navigator)推薦，推薦結果會以「放射式呈現」(Spark Visualization)及「表格地圖」(Tabular Map)的方式表達相關技術資源。此外，為了將內部知識妥善保存以利後續應用，本研究包含了「主題地圖管理平台」，能將知識以主題地圖的形式儲存於關聯式資料庫。

本研究所開發的主題地圖是以符合ISO/IEC 13250國際標準的XTM(XML Topic Maps)格式來描述，符合此格式的主題地圖可支援廣泛的應用，並透過其合併之特性，與其他主題地圖相互更新及擴充。

In 21st century, robots are expected to play more diverse roles to help human beings do more daily tasks. They will not be just seen as mechanical arms in today industry. Multi-functional mechanical pets will produce much market value and make life more fun. In fact, some good design concepts are usually based on existing game robots. Excellent design ideas are always be possible to be found in the existing winner robots. Reusing the design effectively by IT technology is the most exciting and challenging issues in knowledge management domain.

With the help of the Stanford’s Ontology framework, our paper propose a Recommender Agent System to enable the existing design knowledge to be visible though PC’s IE browser and be used effectively with the navigation help. Our agent-based system is started from an existing Content Robot Ontology, regarded as the internal knowledge architecture. The TAO (Topic-Assocation-Occurence) model is then constructed to make clearly robot documents appear as valuable topics of knowledge map. A Topic-Map-based prototype is implemented by the International ISO/IEC 13250 XTM (XML Topic Maps) standard.

In practice, the product design would be started from some simple design concepts. Our recommender agent is proposed here to try to capture the concept query from the interactions with the robot designer. With the classification base of our robot ontology, the search operations can be well navigated and then find out some related documents in few mouse clicks.

Our system can act as a simple Concept Search Engine with the GUI base of two operation modes, Knowledge Vein and Topic Navigator. The recommendation result can be presented by way of Spark Visualization and Tabular Map. In addition, a Topic Map Management Platform is also developed to store knowledge in the relational database in the form of Topic Map.

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