7. An information processing method for constructing an information analysis processing configuration to be applied to information analysis processing in an observation domain including an uncertainty, said information processing method comprising the steps of: generating, with a data processing unit, an intra Bayesian Network for each observation element included in an observation space of a Partially Observable Markov Decision Process; combining, with the data processing unit, a plurality of Bayesian Networks, each generated for one observation element included in said observation space, all of the plurality of as Bayesian Networks having the same event observation domain, in order to construct a combined Bayesian Network; generating, with the data processing unit, a Dynamic Bayesian Network by analyzing relationships between elements in a plurality of combined Bayesian Networks, each of the combined Bayesian Networks corresponding to a different event observation domain, in order to construct a Dynamic Bayesian Network including information on relations between elements in said different event observation domains; and generating, based on the Dynamic Bayesian Network and with the data processing unit, a Factored Partially Observable Markov Decision Process including information on relations between elements pertaining to information spaces of said Partially Observable Markov Decision Process, the information spaces including at least the observation space.
7. An information processing method for constructing an information analysis processing configuration to be applied to information analysis processing in an observation domain including an uncertainty, said information processing method comprising the steps of: generating, with a data processing unit, an intra Bayesian Network for each observation element included in an observation space of a Partially Observable Markov Decision Process; combining, with the data processing unit, a plurality of Bayesian Networks, each generated for one observation element included in said observation space, all of the plurality of as Bayesian Networks having the same event observation domain, in order to construct a combined Bayesian Network; generating, with the data processing unit, a Dynamic Bayesian Network by analyzing relationships between elements in a plurality of combined Bayesian Networks, each of the combined Bayesian Networks corresponding to a different event observation domain, in order to construct a Dynamic Bayesian Network including information on relations between elements in said different event observation domains; and generating, based on the Dynamic Bayesian Network and with the data processing unit, a Factored Partially Observable Markov Decision Process including information on relations between elements pertaining to information spaces of said Partially Observable Markov Decision Process, the information spaces including at least the observation space. 11. The information processing method according claim 7 , further including: inputting element information including the types of elements included in the information spaces as well as Max-Fan-In used as information on the configuration of said Factored Partially Observable Markov Decision Process to show the state of connections of nodes in each Bayesian Network; and constructing the Factored Partially Observable Markov Decision Process in accordance with pieces of said input information.