Data processing: artificial intelligence – Knowledge processing system – Knowledge representation and reasoning technique
Reexamination Certificate
2007-10-30
2009-12-22
Starks, Jr., Wilbert L (Department: 2129)
Data processing: artificial intelligence
Knowledge processing system
Knowledge representation and reasoning technique
C706S045000
Reexamination Certificate
active
07636701
ABSTRACT:
Providing dynamic learning for software agents in a simulation is described. The 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 a player character. A game designer provides program code, from which compile-time steps determine a set of raw features. The code may 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, may 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.
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Cabral Brian
Dobson Daniel
Duffy Nigel
Funge John
McNally Michael
AiLive Inc.
Starks, Jr. Wilbert L
Zheng Joe
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