2. A method as in claim 1 , wherein the steps of presenting collectively include operating a simulation engine having a set of state variables, and having a set of rules describing permitted changes in value of those state variables, wherein substantially each collection of possible values for the set of state variables defines a context; and the set of decision models collectively include a set of behavior models, each capable of responding to a query from the simulation engine and capable of generating a response to that query.
2. A method as in claim 1 , wherein the steps of presenting collectively include operating a simulation engine having a set of state variables, and having a set of rules describing permitted changes in value of those state variables, wherein substantially each collection of possible values for the set of state variables defines a context; and the set of decision models collectively include a set of behavior models, each capable of responding to a query from the simulation engine and capable of generating a response to that query. 14. A method as in claim 2 , including steps of in a computer game having at least one decision model, the decision model being capable of generating a response to a query for decision, generating a response to a query for decision including training one or more non-player characters in response to a set of game results, wherein those game results are produced by at least one of one or more non-player characters or at least one of one or more player characters; wherein actions by those one or more non-player characters are responsive for at least one human user, to at least one of: demographic information, player history, player preferences, player skill, player style.