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。

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）。

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。