"Invention as a search" hypothesis results in application of various search algorithms such as genetic algorithms, simulated annealing etc applied to the process of inventing. One such patent is US 7117186.
The patent describes a method and apparatus for automatic synthesis of controllers. As one can see the problem has been reduced to an optimization problem of finding the right configuration and signal blocks etc to meet specific performance parameters. It is interesting patent and approach, However, one needs to design this for different fields - for example I can not use this for designing a new solar energy system.
Abstract A general automated method for synthesizing the design of both the topology and parameter values for controllers is described. The automated method automatically makes decisions concerning the total number of signal processing blocks to be employed in the controller, the type of each signal processing block, the topological interconnections between the signal processing blocks, the values of all parameters for the signal processing blocks, and the existence, if any, of internal feedback between the signal processing blocks within the controller. The general automated method can simultaneously optimize prespecified performance metrics (such as minimizing the time required to bring the plant outputs to the desired values as measured by the integral of the time-weighted absolute error or the integral of the squared error), satisfy time-domain constraints (such as overshoot, disturbance rejection, limits on control variables, and limits on state variables), and satisfy frequency domain constraints (bandwidth).
When one apply the depth1 citation analysis using Crafitti's methodology implemented at SocialCitNet we get the following network
One can see the base patent that this patent refers to is US 5867397. This patent has been granted to the same inventor and describes genetic programming for automated design of complex structures
Abstract An automated design process and apparatus for use in designing complex structures, such as circuits, to satisfy prespecified design goals, using genetic operations. The present invention uses a population of entities which may be evolved to generate structures that may potentially satisfy the design goals. The behavior of such generated structures is evaluated in view of the design goals, and those structures more closely meeting the design goals are evolved further until a structure is generated that either meets the prespecified design goal or some other process completion criteria. In this manner, a design complex structure may be obtained.
The key to these invention are the bit-string encoding of population in a solution space and searching using fitness function and genetic operators as per GAs.
Now if we do the depth2 analysis of this patent at USPTO using SocialCitNet we get a network of a mind boggling 311 patents
Now how do we choose which of these 311 patents one should study. Visually it may be very difficult. Here the SocialCitNet gives us a remarkable visibility on the relative value of each of these patents in the network - please see the network has 680 connections.
The NDPI - network dependency on patent index gives a relative measure of how much the whole network of 380 patents cites the specific patent - obviously if the network cites the patent more the patent has high relative NDPI
One can see US 5867397 indeed is the base patent on which this network depends. It also shows US 6360191 and US6424959 shown in depth1 network as well. However it gives US5136686 and US5148513
However all the patents are by the same inventor. Clearly it is a field driven by one specific group of researchers. May have potential in future?
Let us see the future - SocialCitNet gives the PDNI indices of all those patents in the network that are citing the more of the network relative to other patents. The belief is if a patent cites more of the network, it is extending the domain and definitely improving the previous inventions. If however, it cites less of the network, it may be using some part of the field or may be an application in some other domain.
US 7940105 stands out sharply, which was available in depth1 network as well. Now look at US7692397 - this was not in depth 1. This one is by Finkler and not shown in depth1 network. Further, it cites, relatively higher relative value of the network. It is imperative for us to study these patents.
From the point of view of a balanced PDNI and NDPI indices SocialCitNet gives a social citation index of the patent
One may argue, what are we getting with so much exploration on a single patent.
One Patent Leading to a network of 311 patents. Then choosing top 20 patents above that if you study you cover the 311 - or the whole space - is it not a considerable time saving and effort saving. I know, inventors searching for new solutions or new problems in patent databases - but SocialCitNet gives you a very well directed focused view of the domain that you are interested in.
You can just start using SOCIALCITNET today!
The patent describes a method and apparatus for automatic synthesis of controllers. As one can see the problem has been reduced to an optimization problem of finding the right configuration and signal blocks etc to meet specific performance parameters. It is interesting patent and approach, However, one needs to design this for different fields - for example I can not use this for designing a new solar energy system.
When one apply the depth1 citation analysis using Crafitti's methodology implemented at SocialCitNet we get the following network
One can see the base patent that this patent refers to is US 5867397. This patent has been granted to the same inventor and describes genetic programming for automated design of complex structures
The key to these invention are the bit-string encoding of population in a solution space and searching using fitness function and genetic operators as per GAs.
Now if we do the depth2 analysis of this patent at USPTO using SocialCitNet we get a network of a mind boggling 311 patents
| Patent: | 7117186 |
| Database: | USPTO |
| Depth: | 2 |
| No. of Nodes: | 311 | |||
| No. Of Connections: | 680 | |||
| Sparsity of Graph: | 0.0102 |
Now how do we choose which of these 311 patents one should study. Visually it may be very difficult. Here the SocialCitNet gives us a remarkable visibility on the relative value of each of these patents in the network - please see the network has 680 connections.
The NDPI - network dependency on patent index gives a relative measure of how much the whole network of 380 patents cites the specific patent - obviously if the network cites the patent more the patent has high relative NDPI
One can see US 5867397 indeed is the base patent on which this network depends. It also shows US 6360191 and US6424959 shown in depth1 network as well. However it gives US5136686 and US5148513
However all the patents are by the same inventor. Clearly it is a field driven by one specific group of researchers. May have potential in future?
Let us see the future - SocialCitNet gives the PDNI indices of all those patents in the network that are citing the more of the network relative to other patents. The belief is if a patent cites more of the network, it is extending the domain and definitely improving the previous inventions. If however, it cites less of the network, it may be using some part of the field or may be an application in some other domain.
US 7940105 stands out sharply, which was available in depth1 network as well. Now look at US7692397 - this was not in depth 1. This one is by Finkler and not shown in depth1 network. Further, it cites, relatively higher relative value of the network. It is imperative for us to study these patents.
From the point of view of a balanced PDNI and NDPI indices SocialCitNet gives a social citation index of the patent
One may argue, what are we getting with so much exploration on a single patent.
One Patent Leading to a network of 311 patents. Then choosing top 20 patents above that if you study you cover the 311 - or the whole space - is it not a considerable time saving and effort saving. I know, inventors searching for new solutions or new problems in patent databases - but SocialCitNet gives you a very well directed focused view of the domain that you are interested in.
You can just start using SOCIALCITNET today!
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