Query controlled behavior models as components of intelligent agents
First Claim
1. In a computer system including a simulation engine having a set of state variables, and wherein a collection of possible values for at least some of those state variables defines a context, a method including steps of:
- defining a set of behavior models, each capable of receiving queries from the simulation engine and generating responses to those queries;
defining a set of software agents, each being responsive to one or more of those behavior models, and each capable of being updated in response to changes from a first context to a second context;
presenting a sequence of states, each possible such state defining a context, the steps of presenting including operating a set of software agents within a set of rules for the steps of presenting; and
generating a response to a query for decision by at least one of a set of decision models;
wherein at least one of the software agents is responsive to one or more decision models, and is capable of being updated in response to changes from a first context to a second context.
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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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Citations
17 Claims
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1. In a computer system including a simulation engine having a set of state variables, and wherein a collection of possible values for at least some of those state variables defines a context, a method including steps of:
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defining a set of behavior models, each capable of receiving queries from the simulation engine and generating responses to those queries; defining a set of software agents, each being responsive to one or more of those behavior models, and each capable of being updated in response to changes from a first context to a second context; presenting a sequence of states, each possible such state defining a context, the steps of presenting including operating a set of software agents within a set of rules for the steps of presenting; and generating a response to a query for decision by at least one of a set of decision models; wherein at least one of the software agents is responsive to one or more decision models, and is capable of being updated in response to changes from a first context to a second context. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17)
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Specification