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    • 15. 发明授权
    • Method and system for rapid evaluation of logical expressions
    • 逻辑表达式快速评估的方法和系统
    • US07636697B1
    • 2009-12-22
    • US11699201
    • 2007-01-29
    • Daniel DobsonJohn FungeCharles MusickStuart ReynoldsXiaoyuan TuIan WrightWei Yen
    • Daniel DobsonJohn FungeCharles MusickStuart ReynoldsXiaoyuan TuIan WrightWei Yen
    • G06F15/18
    • G06N99/005
    • Methods and systems capable of determining which subset of a set of logical expressions are true with relatively few evaluations of the primitives that, together with any standard logical connectives, make up the logical expressions. A plurality of directed acyclic graphs, each graph including at least one root node, at least one leaf node, and at least one non-leaf node associated with a leaf node. Each node is associated with a, possibly empty, subset of presumed to be true logical expressions. Each non-leaf node is associated with one of the primitives mentioned in any of the logical expressions. Edges are defined between two of the nodes, each edge being associated with a possible value, or range of possible values, of the primitive associated with the node at the tail of the edge. Paths are defined through each of the directed acyclic graphs from a root node to a leaf node by recursively following each edge corresponding to the current value of the primitive at a selected non-leaf node. Lastly, subsets of logical expressions associated with the nodes on the defined paths are collated to yield a subset of logical expressions that are true.
    • 能够通过相对较少的原语评估来确定一组逻辑表达式的哪个子集的方法和系统以及任何标准逻辑连接符构成逻辑表达式。 多个有向无环图,每个图包括至少一个根节点,至少一个叶节点和与叶节点相关联的至少一个非叶节点。 每个节点与假设为真逻辑表达式的可能为空的子集相关联。 每个非叶节点与任何逻辑表达式中提到的原语之一相关联。 在两个节点之间定义边缘,每个边缘与与边缘尾部的节点相关联的基元的可能值或可能值的范围相关联。 通过在选定的非叶节点处递归地跟随对应于原语的当前值的每个边缘,通过从根节点到叶节点的每个有向无环图来定义路径。 最后,与定义的路径上的节点相关联的逻辑表达式的子集进行整理,以产生真实的逻辑表达式的子集。
    • 17. 发明申请
    • REAL TIME CONTEXT LEARNING BY SOFTWARE AGENTS
    • 软件代理的实时语境学习
    • US20070260567A1
    • 2007-11-08
    • US10885495
    • 2004-07-06
    • John FungeRon MusickDaniel DobsonNigel DuffyMichael McNallyXiaoyuan TuIan WrightWei YenBrian Cabral
    • John FungeRon MusickDaniel DobsonNigel DuffyMichael McNallyXiaoyuan TuIan WrightWei YenBrian Cabral
    • G06F17/00
    • A63F13/67A63F13/10A63F2300/60A63F2300/6027G06N99/005
    • Providing dynamic learning for software agents in a simulation. Software agents with learners are capable of learning from examples. When a non-player character queries the learner, it can provide a next action similar to the player character. The game designer provides program code, from which compile-time steps determine a set of raw features. The code might identify a function (like computing distances). At compile-time steps, determining these raw features in response to a scripting language, so the designer can specify which code should be referenced. A set of derived features, responsive to the raw features, might be relatively simple, more complex, or determined in response to a learner. The set of such raw and derived features form a context for a learner. Learners might be responsive to (more basic) learners, to results of state machines, to calculated derived features, or to raw features. The learner includes a machine learning technique.
    • 在模拟中为软件代理提供动态学习。 具有学习者的软件代理能够从示例中学习。 当非玩家角色查询学习者时,它可以提供类似于玩家角色的下一个动作。 游戏设计师提供程序代码,编译时步骤确定一组原始特征。 代码可能会识别一个函数(如计算距离)。 在编译时步骤中,根据脚本语言确定这些原始特征,因此设计人员可以指定哪些代码应该被引用。 响应于原始特征的一组派生特征可能相对简单,更复杂或响应于学习者而确定。 这些原始和派生特征的集合形成了学习者的上下文。 学习者可以对(更基础的)学习者,状态机的结果,计算的导出特征或者原始特征进行响应。 学习者包括机器学习技术。