A system for adaptive intelligent decision making includes circuitry that receives a spatiotemporal problem that includes at least one of a spatial dimension and a temporal dimension. Problem data is assigned to a relative problem space that affects decisions to the spatiotemporal problem. Weighting factors are assigned to the problem data that indicate an effect of the problem data on the decisions to the spatiotemporal problem in order to control relationships between the problem data in the relative problem space. Decisions are determined to the spatiotemporal problem based on decisions between the problem data. Feedback is provided that is related to the decisions and an associated decision confidence factor.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A system for adaptive intelligent decision making, comprising: circuitry configured to: receive a spatiotemporal problem that includes at least one of a spatial dimension and a temporal dimension, assign problem data that affect one or more decisions to the spatiotemporal problem to a relative problem space, assign weighting factors indicating an effect of the problem data on the one or more decisions to the spatiotemporal problem to control relationships between the problem data in the relative problem space, determine the one or more decisions to the spatiotemporal problem based on the relationships between the problem data, and provide feedback related to the one or more decisions and an associated decision confidence factor. 2. The system for adaptive intelligent decision making of claim 1, wherein the problem data in the relative problem space includes problem variables, spatiotemporal variables, fuzzy information, fuzzy knowledge, and relative space knowledge. 3. The system for adaptive intelligent decision making of claim 2, wherein the circuitry is further configured to determine data variable impact weights for the problem variables based on effects of the problem variables on the one or more decisions. 4. The system for adaptive intelligent decision making of claim 3, wherein the circuitry is further configured to determine data variable quality weights for the problem variables based on at least one of a completeness and robustness of the problem variables. 5. The system for adaptive intelligent decision making of claim 4, wherein the circuitry is further configured to determine variable selection probability weights for the problem variables based on the data variable impact weights and the data variable quality weights. 6. The system for adaptive intelligent decision making of claim 3, wherein the circuitry is further configured to determine spatiotemporal impact weights for the problem variables based on effects of the spatiotemporal variables on the problem variables. 7. The system for adaptive intelligent decision making of claim 6, wherein the circuitry is further configured to determine spatiotemporal impacts on the variable weight direction based on directions and magnitudes of change in the data variable impact weights when the spatiotemporal variables are modified. 8. The system for adaptive intelligent decision making of claim 2, wherein the fuzzy knowledge includes one or more knowledge rules or associations between the problem data in the relative problem space. 9. The system for adaptive intelligent decision making of claim 8, wherein the circuitry is further configured to determine average rule decision variable impact weights for the fuzzy knowledge based on an effect of the problem variables on the one or more knowledge rules. 10. The system for adaptive intelligent decision making of claim 9, wherein the circuitry is further configured to determine rule impact weights for the one or more knowledge rules based on effects of the one or more knowledge rules on the one or more decisions. 11. The system for adaptive intelligent decision making of claim 10, wherein the circuitry is further configured to determine rule selection probability weights for the one or more knowledge rules based on the average rule decision variable impact weights and the rule impact weights. 12. The system for adaptive intelligent decision making of claim 11, wherein the circuitry is further configured to determine rule selection probability weights based on the rule selection probability weights and average of probability selection weights for the problem variables in the one or more knowledge rules. 13. The system for adaptive intelligent decision making of claim 1, wherein the circuitry is further configured to determine the one or more decisions based on one or more rule selection probability weights that are greater than a predetermined threshold. 14. The system for adaptive intelligent decision making of claim 1, wherein the one or more decisions include spatiotemporal values, variables, and the weighting factors that affected the one or more decisions. 15. The system for adaptive intelligent decision making of claim 1, wherein the circuitry is further configured to determine the decision confidence factor based on a decision inference degree and an external feedback confidence degree. 16. The system for adaptive intelligent decision making of claim 15, wherein the circuitry is further configured to determine the decision inference degree based on a confidence level in the one or more decisions. 17. The system for adaptive intelligent decision making of claim 16, wherein the circuitry is further configured to determine the external feedback confidence degree based on a measured effectiveness of the one or more decisions in practice. 18. The system for adaptive intelligent decision making of claim 1, wherein the circuitry is further configured to modify the problem data in the relative problem space based on the feedback regarding the one or more decisions. 19. A non-transitory computer-readable medium having computer-readable instructions thereon which when executed by a computer cause the computer to perform a method for solving spatiotemporal-based problems, the method comprising: receiving a spatiotemporal problem that includes at least one of a spatial dimension and a temporal dimension; assigning problem data that affect one or more decisions to the spatiotemporal problem to a relative problem space; assigning weighting factors indicating an effect of the problem data on the one or more decisions to the spatiotemporal problem to control relationships between the problem data in the relative problem space; determining the one or more decisions to the spatiotemporal problem based on the relationships between the problem data; and providing feedback regarding the decision and an associated decision confidence factor. 20. A method for solving spatiotemporal-based problems, comprising: receiving, at least one server, a spatiotemporal problem that includes at least one of a spatial dimension and a temporal dimension; assigning, at the at least one server, problem data that affect one or more decisions to the spatiotemporal problem to a relative problem space; assigning, at the at least one server, weighting factors indicating an effect of the problem data on the one or more decisions to the spatiotemporal problem to control relationships between the problem data in the relative problem space; determining, at the at least one server, the one or more decisions to the spatiotemporal problem based on the relationships between the problem data; and providing, at the at least one server, feedback regarding the decision and an associated decision confidence factor.