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    A SYSTEM AND METHOD FOR DETERMINING PRODUCTION PLANS AND FOR PREDICTING INNOVATION
    1.
    发明申请
    A SYSTEM AND METHOD FOR DETERMINING PRODUCTION PLANS AND FOR PREDICTING INNOVATION 审中-公开
    一种用于确定生产计划和预测创新的系统和方法

    公开(公告)号：WO0020983A8

    公开(公告)日：2000-07-20

    申请号：PCT/US9922911

    申请日：1999-10-01

    Applicant: BIOS GROUP LP ,  AUERSWALD PHILIP ,  KAUFFMAN STUART A ,  LOBO JOSE ,  SHELL KARL

    Inventor： AUERSWALD PHILIP ,  KAUFFMAN STUART A ,  LOBO JOSE ,  SHELL KARL

    IPC: G06Q10/00 ,  G06F17/60

    CPC classification number: G06Q10/06

    Abstract: The present invention relates generally to design and evaluation of research and development, technology transfer, and learning-by-doing, and more particularly to the determination of production plans and the prediction of innovation. A preferred embodiment comprises a method for determining a production plan comprising the steps of: defining a plurality of production recipes such that each of said production recipes is a vector of n operations; selecting a current one of the production recipes; evaluating the current production recipe to determine its cost; modifying the current production recipe to create a trial production recipe (130); evaluating the trial production recipe to determine its cost (140, 150); and assigning the trial production recipe to the current production recipe if the cost of the trial production recipe is less than the cost of the current production recipe.

    Abstract translation: 本发明一般涉及研究开发，技术转让和学习的设计与评估，特别涉及生产计划的确定和创新的预测。 优选实施例包括用于确定生产计划的方法，包括以下步骤：定义多个生产配方，使得每个所述生产配方是n个操作的向量; 选择当前的生产食谱之一; 评估当前的生产配方以确定其成本; 修改当前生产食谱以创建试生产食谱（130）; 评估试生产配方以确定其成本（140,150）; 并且如果试生产配方的成本小于当前生产配方的成本，则将试生产配方分配给当前生产配方。

    AUTOMATIC EVOLUTION OF MIXED ANALOG AND DIGITAL ELECTRONIC CIRCUITS
    2.
    发明申请
    AUTOMATIC EVOLUTION OF MIXED ANALOG AND DIGITAL ELECTRONIC CIRCUITS 审中-公开
    混合模拟和数字电子电路的自动演进

    公开(公告)号：WO0019369A8

    公开(公告)日：2000-07-13

    申请号：PCT/US9922917

    申请日：1999-10-01

    Applicant: BIOS GROUP LP ,  HERRIOT JAMES W ,  KAUFFMAN STUART A

    Inventor： HERRIOT JAMES W ,  KAUFFMAN STUART A

    IPC: G06N3/00 ,  G06F15/00 ,  G06F15/18

    CPC classification number: G06N3/004

    Abstract: A method and system for evolving electronic circuits based on defined rules. A first approach uses a network (50) of nodes (60) having established topological and behavioral relationships amongst themselves. A second approach employs software agents to create signal filters. The software agents are allowed to evolve in signal parameter space so as to match a reference signal (200), subject to established evolutionary rules and parameter space constraints. Narrowband and a low-pass filter can be formed using such agents.

    Abstract translation: 基于定义规则演进电子电路的方法和系统。 第一种方法使用其间具有已建立的拓扑和行为关系的节点（60）的网络（50）。 第二种方法使用软件代理来创建信号过滤器。 允许软件代理在信号参数空间中进化，以便匹配参考信号（200），受制于进化规则和参数空间限制。 可以使用这样的试剂形成窄带和低通滤波器。

    A METHOD FOR OPTIMAL SEARCH ON A TECHNOLOGY LANDSCAPE
    3.
    发明申请
    A METHOD FOR OPTIMAL SEARCH ON A TECHNOLOGY LANDSCAPE 审中-公开
    一种对技术景观进行最佳搜索的方法

    公开(公告)号：WO0013072A3

    公开(公告)日：2000-06-29

    申请号：PCT/US9919916

    申请日：1999-08-31

    Applicant: BIOS GROUP LP ,  KAUFFMAN STUART A ,  LOBO JOSE ,  MACREADY WILLIAM G

    Inventor： KAUFFMAN STUART A ,  LOBO JOSE ,  MACREADY WILLIAM G

    IPC: G06F17/10 ,  G06Q10/00 ,  G06F9/455 ,  G06F17/11 ,  G06F17/50

    CPC classification number: G06Q10/04 ,  G06Q30/0283

    Abstract: Technological change at the film-level has commonly been modeled as random sampling from a fixed distribution of possibilities. Such models, however, typically ignore empirically important aspects of the firm's search process, notably the observation that the present state of the firm guides future innovation. We explicitly treat this aspect of the firm's search for technological improvements by introducing a "technology landscape" (Fig. 6) into an otherwise standard dynamic programming setting where the optimal strategy is to assign a reservation price to each possible technology. Search is modeled as movement, constrained by the cost of innovation, over the technology landscape. Simulations (Fig. 6) are presented on a stylized technology landscape while analytic results are derived using landscapes that are similar to Markov random fields.

    Abstract translation: 电影级别的技术变革通常被模拟为从固定分配可能性的随机抽样。 然而，这种模式通常忽略了企业搜索过程的实证重要方面，特别是对企业目前状况指导未来创新的观察。 我们通过将“技术环境”（图6）引入到其他标准的动态规划设置中，明确地对待公司寻求技术改进的方面，其中最佳策略是为每个可能的技术分配预留价格。 搜索被建模为运动，受创新成本的限制，超过了技术格局。 模拟（图6）呈现在风格化的技术景观上，而分析结果是使用与马尔可夫随机场相似的景观得出的。

    A METHOD AND SYSTEM FOR ROUTING CONTROL IN COMMUNICATION NETWORKS AND FOR SYSTEM CONTROL
    5.
    发明申请
    A METHOD AND SYSTEM FOR ROUTING CONTROL IN COMMUNICATION NETWORKS AND FOR SYSTEM CONTROL 审中-公开
    一种用于在通信网络中进行路由控制和用于系统控制的方法和系统

    公开(公告)号：WO0045584A8

    公开(公告)日：2000-11-02

    申请号：PCT/US0002011

    申请日：2000-01-28

    Applicant: BIOS GROUP LP ,  KAUFFMAN STUART A ,  PLATE TONY A

    Inventor： KAUFFMAN STUART A ,  PLATE TONY A

    IPC: H04L12/701 ,  H04L12/721 ,  H04L12/725 ,  H04M15/00 ,  G06F15/18 ,  H04L12/46

    CPC classification number: H04L45/12 ,  H04L45/00 ,  H04L45/308

    Abstract: The present invention relates generally to a method and system for routing control in communication networks and for system control. More particularly, the present invention performs routing by controlling the components in a network with software agents (102) operating in a reward framework using p, tau, and patches (104) to improve communication performance (106). This invention disclosure includes the combination of reinforcement learning agents in a market-based or performance-based reward framework together with optimization techniques called p, tau, and patches (104) as applied to the problem of topology-and load-based routing in data networks, in order to improve communication performance (106) such as communication latency and bandwidth. The invention also applies to the control of other systems, including operations management, job-shop problems, organizational structure, portfolio management, risk management etc.

    Abstract translation: 本发明一般涉及用于通信网络中的路由控制和系统控制的方法和系统。 更具体地说，本发明通过使用p，tau和补丁（104）在奖励框架中运行的软件代理（102）控制网络中的组件来执行路由，以改善通信性能（106）。 本发明公开内容包括基于市场或基于性能的奖励框架中的强化学习代理的组合以及被应用于数据中的基于拓扑和基于负载的路由问题的被称为p，tau和补丁（104）的优化技术 网络，以便改善诸如通信等待时间和带宽的通信性能（106）。 本发明也适用于其他系统的控制，包括运营管理，作业问题，组织结构，投资组合管理，风险管理等。

    A METHOD FOR PREDICTING PRODUCT DEMAND USING SELF-ORGANIZING DEMAND LOOPS
    6.
    发明申请
    A METHOD FOR PREDICTING PRODUCT DEMAND USING SELF-ORGANIZING DEMAND LOOPS 审中-公开
    一种使用自组织需求量预测产品需求的方法

    公开(公告)号：WO0067191A3

    公开(公告)日：2007-06-14

    申请号：PCT/US0012471

    申请日：2000-05-05

    Applicant: BIOS GROUP LP ,  KAUFFMAN STUART A ,  HERRIOT JAMES W ,  DARLEY VINCE A

    Inventor： KAUFFMAN STUART A ,  HERRIOT JAMES W ,  DARLEY VINCE A

    IPC: G06F17/30 ,  G06Q30/00

    CPC classification number: G06Q30/02

    Abstract: The present invention relates generally to a system and method for predicting future demand for goods and/or services ( 100). More specifically, the invention provides a system and method for predicting future demand ( 106) for goods and/or services based on information obtained from offering for sale options for the goods and/or services at different levels of product, regional and temporal hierarchies (104).

    Abstract translation: 本发明一般涉及用于预测未来对商品和/或服务的需求的系统和方法（100）。 更具体地说，本发明提供了一种系统和方法，用于基于从产品，区域和时间层级的不同级别的商品和/或服务的出售选项提供的信息来预测商品和/或服务的未来需求（106） 104）。

    A SYSTEM AND METHOD FOR MOLECULE SELECTION USING EXTENDED TARGET SHAPE
    7.
    发明申请
    A SYSTEM AND METHOD FOR MOLECULE SELECTION USING EXTENDED TARGET SHAPE 审中-公开
    使用扩展目标形状的分子选择的系统和方法

    公开(公告)号：WO0063421A9

    公开(公告)日：2002-06-06

    申请号：PCT/US0010484

    申请日：2000-04-19

    Applicant: BIOS GROUP LP ,  KAUFFMAN STUART A ,  LEVITAN BENNETT S

    Inventor： KAUFFMAN STUART A ,  LEVITAN BENNETT S

    IPC: C07B61/00 ,  C40B30/02 ,  G01N33/68 ,  G06F19/00 ,  G06F19/16 ,  G06F19/24 ,  C12Q1/00 ,  C07H21/02 ,  C12P19/24 ,  C12P21/06 ,  C12Q1/68 ,  G01N33/48 ,  G01N33/50

    CPC classification number: G06F19/16 ,  C40B30/02 ,  C40B50/02 ,  G01N33/6803 ,  G01N2500/00 ,  G06F19/24 ,  G06F19/704

    Abstract: The present invention is directed to production of a molecule having a predetermined property. In accordance with one embodiment, a library of initial candidate molecules that are at least somewhat dissimilar to a chosen target molecule or "targetshape" is generated. Variants of the initial candidates are generated and screened to identify intermediate candidates from among those variants that are either more or less similar to the targetshape. Data mining techniques such as neural networks are used to extract information about the molecule structures and shapes which lead to the desired activity. Molecular data bases may be screened for candidates matching the preferred shape description or molecules matching the preferred shape description may be synthesized. The process may be iterated by generating variants of the intermediate candidates and screening these variants to identify molecules futher more or less similar to the targetshape.

    Abstract translation: 本发明涉及具有预定特性的分子的制备。 根据一个实施方案，产生至少在某种程度上不同于所选择的靶分子或“靶标形状”的初始候选分子的文库。 生成和筛选初始候选人的变体，以从与目标形状大致相似的那些变体中识别中间候选。 使用诸如神经网络的数据挖掘技术来提取关于导致所需活动的分子结构和形状的信息。 可以筛选与优选形状描述匹配的候选物的分子数据库，或者可以合成优选形状描述匹配的分子。 可以通过产生中间候选物的变体并筛选这些变体来鉴定或多或少与靶标相似的分子来迭代该过程。

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