IEEE proceedings of International Conference on MEMS, NANO and Smart Systems, July 2003, pp274-278
Computational Patent Mapping: Intelligent Agents for Nanotechnology Tralvex YEAP 3i Analytics
[email protected] Gim Hwa LOO 3i Analytics
[email protected] Serena PANG 3i Analytics
[email protected] system. Among the diverse applications of nanotechnology [5,9,10], those that involve multi-agents system consist of nano-medicine, defense, materials and manufacturing, environment, agriculture and space development [6,11,12,13].
Abstract Patents are an important source of technological intelligence that companies can use to gain strategic advantage and computational patent mapping is a methodology for the development and application of a technology knowledgebase for technology and competitive intelligence. The primary deliverables of patent mapping is in the form of knowledge visualization through landscape and maps. This paper applied computational patent mapping techniques in the area of nanoagent and several dominant nanoagent themes have been identified by the visualization of a patent dataset presented in the form of a patent landscape for nanoagents. This study reveal insights into nanoagents patent technology S-curves, patenting activities of various nanoagent players over time, the development in nanoagent enabling technologies over time and selected patent with high QS-Index.
2. Patent Analysis and Mapping The World Intellectual Property Organisation revealed that 90% to 95% of all the world’s inventions are found in patented documents. Additionally, the European Patent Office also disclosed that "patents reveal solutions to technical problems, and they represent an inexhaustible source of information: more than 80 percent of man's technical knowledge is described in patent literature." In this series of computation patent analysis and mapping, we showcase technology intelligence in the area of nanoagent. There are three levels of detail in the computational patent analysis [14] and mapping process (Figure 1):
Keywords: Patents, Computational Patent mapping, Patent Analysis, Technology Intelligence, Intelligent Agents, Nanotechnology, Nanoscience, Competitive Intelligence.
1. Introduction Nanotechnology is the creation and application of materials and devices at the level of atoms and molecules, as well as the exploitation of its unique properties and phenomena of matter at the nanoscale. In Engines of Creation [1] and Our Molecular Future: How Nanotechnology, Robotics, Genetics and Artificial Intelligence Will Transform Our World [2], both authors postulated the role of intelligent agents in nanotechnology, henceforth known as nanoagents. In simplicity, an intelligent agent is an entity, which has capabilities to deal with new and trying situations having characteristics of being autonomous and rational [3] and a nanoagent is an intelligent agent that operates in nanoscale. In complex applications involving real-world interaction with animated and in-animated objects, such as industrial, commercial, medical and entertainment domains [4] engaging interaction between a group of intelligent agents or typically known as multi-agents
Figure 1. Patent analysis, level of details Level 1: At 80,000 feet, a visualization of the nanoagents patent documents is presented in the form of a patent landscape, highlighting dominant themes within the patent dataset; Level 2: At 50,000 feet, various results of patent analysis are further distilled into patent maps for the ease of comprehension; and
1
IEEE proceedings of International Conference on MEMS, NANO and Smart Systems, July 2003, pp274-278
version) for the diffusion of patent innovation [8] in nanoagent technology. The very first nanoagent patent appeared in 1993 (P1), followed by a gradual growth in the patent count for three years. P2 marks the transition from gradual growth to rapid growth which lasted for only two short years when its growth rate was acutely reduced (P3) back to gradual-slow growth. This phenomenon is rather unusual to us as from our past patent analysis and mapping projects, 96% of the Scurves for different technologies did not exhibit a “fallback” growth - rapid growth to gradual growth. The inference we draw from here is that nanoagent patent technology is reaching saturation and unless there is some breakthrough in nanoagent technology, this current trend of slower growth will continue. A computation on the nanoagent patent dataset shows that it takes an average of 3.23 years for a nanoagent patent to be granted in USPTO. Thus, our short-term projection for the current trend starts from P4 and we are expecting continuation of the gradual growth which could be further impeded by the shrinking research and development budget caused by the severe worldwide economic downturn since mid-2000.
Level 3: At the ground level, specific patent documents that are of special interest are highlighted.
3. Nanoagents Patent Landscape A patent search in the US Patent Trademark and Office (USPTO) database using Technology Concept Hierarchy strategy for nanoagents revealed that since 1993, there are 416 nanoagent patents. An information visualization of this patent dataset is presented in a patent landscape form (Figure 2, see Annex for enlarged version). As evident in the landscape, there are several dominant nanoagent themes and the three key themes are: 1. Distributed agent technology; 2. Multi-computing agents; and 3. Agents utilizing client/server technology.
P4 P3
P2
Figure 2. Nanoagents patent landscape P1 Table 1. Nanoagents patent landscape
Figure 3. Nanoagent Patent Technology S-Curve
Patent Landscape Guide • Each hill represents a concentration of patent documents of a related theme. • A white shaded peak indicates a higher concentration of patent documents as compared to a gray shaded peak. • Labels on the peak of each hill signify themes. • Each black dot on the map represents a cluster of documents. • The proximity between objects (patent documents and hills) in the patent landscape is directly related the strength of relationships between them.
Big players are defined as large organizations that are into various technology businesses, including nanoagent technology, while pure players are organizations that focused specifically on nanoagent technology. Interesting insights from Figure 4: • There are a total of 192 nanoagent players; • Two notable commercial nanoagent companies, within the dataset but not shown in Figure 4 are: 1. Sentar, Inc; and 2. Inference Corporation (acquired by eGain); • Three big players: IBM, AC Properties and InterTrust Technologies; and • Individuals as a group form the second largest entity in terms of patent count.
4. Nanoagents Patent Maps Patent Technology S-Curve [7] revealed the various stages (Figure 3, P1 to P4 – see Annex for enlarged
2
IEEE proceedings of International Conference on MEMS, NANO and Smart Systems, July 2003, pp274-278
Individual patents are not assigned to any company, thus technology companies that wish to own nanoagent related patents can consider approaching individual inventors to acquire the patent rights for further in-house exploitation and commercialization.
Further analysis and intelligence gathering would reveal more insights into the technology and business strategies that these companies have for their patents portfolio. Figure 6 shows the patenting activities of various nanoagents enabling technologies over time. Three immediate regions of interest are R1, R2 and R3. The technologies in Figure 6 are sorted using QS Transform onto the original dataset. A QS Transform allowed us to automatically surface significant trends peculiar to patent dataset. Current top three nanoagent enabling technologies are distributed computing, multicomputing and client/server technology. The first nanoagent enabling technology involved the use of multi-computing techniques (R1) and majority of the nanoagent activities starts in the year 1995 (R2). As highlighted in the earlier section, the average time taken for a nanoagent patent to be processed is 3.23 years and based on these findings, we can further infer from Figure 6 that all of the mentioned enabling technologies, particularly one that involved knowledge processing system would have a gradual continuity in their research activities.
Figure 4. Big and Pure Patent Assignees Figure 5. shows the patenting activities of various nanoagents players over time. Three immediate regions region of interest labeled as R1, R2 and R3 are highlighted for further explanation. Two related nanoagent research groups within IBM are “Artificial Intelligence” and “Mobile Computing” group.
R3 R1
R2 R1
R2
R3 Figure 6. Nanoagent enabling Technologies over Time Figure 5. Nanoagent Companies Activity over Time There is a noticeable decrease in nanoagent patents (R1) coming out from IBM research group, suggesting a reduction in new research findings or resources within the company. There is also a noticeable spike (R2) in the number of nanoagent patents granted to InterTrust Technologies during the boom time of the dot-com days. Lastly, the emerging players in this field are Tacit Knowledge System, Accenture and Research in Motion.
3
IEEE proceedings of International Conference on MEMS, NANO and Smart Systems, July 2003, pp274-278
QS-Index [14] measures the value of each patent qualitatively, in comparison to other patents in the dataset. Table 2. list five top QS-Index patents from the nanoagent dataset. It is most interesting to note that the top ranking QS-Index patent belongs to an individual, Benjamin, Slotznick. One notable patent in the list is US5,963,447 titled “Multi-agent hybrid control architecture for intelligent real-time control of distributed nonlinear process” by Hynomics Corporation (Figure 7).
5. Conclusion and the Road Ahead In conclusion, we covered technology intelligence in the form of patent landscape as well as various significant patent maps for nanoagent technology. The projected nanoagent patenting trend is likely to be between gradual to slow growth, unless there is a breakthrough in the enabling nanoagent technology.
Table 2. Nanoagent enabling Technologies over Time
There are several other techniques that can be use in the computational patent analysis and mapping projects which have applications in supporting of commercialization and IP valuation. For readers who are interested to receive updates and complementary copies of some of our published computational patent analysis and mapping paper, reports and books can email us at
[email protected].
10. References [1] E. Drexler, Engines of Creation: The Coming Era of Nanotechnology, Anchor, 1987. [2] D. Mulhall, Our Molecular Future: How Nanotechnology, Robotics, Genetics and Artificial Intelligence Will Transform Our World, Prometheus Books, 2002. [3] T. Yeap, Artificial Intelligence: Intelligent Agents and Multiagent Systems, University of London, Singapore, 1999. [4] N.R. Jennings and M. Wooldridge, “Applications of Intelligent Agents”, in Agent Technology: Foundations, Applications, and Markets, Springer, 1998. [5] R. Kurzweil, The Age of Spiritual Machines: When Computers Exceed Human Intelligence, Penguin USA, 2000. [6] NSF/DOC, “Converging Technologies for Improving Human Performance: Nanotechnology, Biotechnology, Information Technology and Cognitive Science”, National Science Foundation/Department of Commerce, 2002. [7] T. Yeap, “Patent Analysis and Mapping: Face Recognition Technology for Airport Surveillance Applications”, ECMS Publication, Singapore, 2002.
Figure 7. US Patent 5,963,447, diagram showing actions performed by individual agents to synchronize distributed, real-time systems.
[8] T. Yeap, Information Systems for Managers - Diffusion of Innovation, University of Southern Queensland, Singapore, 1998. [9] H. Brody, “10 Emerging Technologies That Will Change the World”, Technology Review, 2003. [10] P. Holister, Nanotech, the tiny revolution, CMP Cientifica, 2002.
4
IEEE proceedings of International Conference on MEMS, NANO and Smart Systems, July 2003, pp274-278
[11] M.C. Roco, “Office of Science and Technology Policy, National Nanotechnology Investment", in FY 2002 Budget Request by the President, United States of America, 2001. [12] M.C. Roco, “Office of Science and Technology Policy, "National Nanotechnology Investment", in FY 2003 Budget Request by the President, United States of America, 2002. [13] M.C. Roco, “Office of Science and Technology Policy, National Nanotechnology Initiative", Research and Development Funding in the President's 2004 Budget, United States of America, 2003. [14] A. Blattman, S. Chandran, S. Irani, T. Yeap, D. Perkins, and R. Miller, “Computational Patent Mapping”, in Technology Intelligence and Selected Topics in Biotechnology Patents, ECMS, Singapore, 2003, pp. 5-8.
5
IEEE proceedings of International Conference on MEMS, NANO and Smart Systems, July 2003, pp274-278
6
IEEE proceedings of International Conference on MEMS, NANO and Smart Systems, July 2003, pp274-278
7