A method and system for anticipating the actions of individuals and the occurrence of natural events are disclosed. The anticipatory information system (AIS) stores information using specific and unique methods and applies unique methods to evaluate and identify the upcoming actions of individuals or the upcoming occurrence of natural events based on unique analysis methods applied to existing action and event information, previous action and event stored information, information about nearby and influential actions and the application of a method for determining and ranking the likelihood of an actions occurrence and options for mitigating the resulting effect of such actions.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A system and methods, comprising: performing, by one or more computing devices: determining the upcoming actions of an individual (target entity) based on a unique analysis of stored information about the target entity's actions and the actions and activities of other nearby entities or other entities or natural actions or events based on an analysis of stored information about such actions (analysis of actions) that would affect the target entity's actions or natural event and that is stored with additional information and variables including numerical representations of textual data and categorization unique to the anticipation analysis process methods, wherein the system uses such information and additional information about all actions to anticipate and produce the next anticipated actions of a target entity or natural event and a probability of occurrence for each action, and wherein the action of the target entity is stored using methods to improve the accuracy of the next anticipated action and wherein the anticipated action or event is stored along with the actual results including information and variables unique to the anticipation analysis methods and wherein natural event information and data are stored with information and variables unique to the anticipation analysis methods. 2. The method as recited in claim 1, wherein determining the upcoming action of a target entity (individual) comprises the analysis of a target entity's past actions and the actions of other entities that would impact the target entity's future actions (action of other entities) or the target entity's reaction to a unknown occurring natural event. 3. The method as recited in claim 1, wherein determining the upcoming natural event comprises the analysis of past natural events that would impact the future natural events or reaction to a natural event by an individual or target entity as recorded by external sensors input data. 4. The method as recited in claim 1, wherein the information of prior actions and natural events are stored in a database with additional information and variables unique to the methods used to analyze the information for the purposes of determining the target entity's next action and series of next sequential actions including numerical representations of textual data and categorization. 5. The method as recited in claim 1, wherein the actions of a target entity is analyzed using stored information of a target entity's actions, natural events and the actions of other entities to determine and assign impact variables that define the level of risk and probability of occurrence of each action or event and wherein such information is stored with additional information and variables unique to the analysis and determination of a next anticipated action or series of sequential actions (action stream or action string). 6. The method as recited in claim 1, wherein the anticipated actions of a target entity or the anticipated actions of other entities or natural events that would impact a target entity are stored with additional information and variables unique to the analysis of actions including numerical representations of textual data and categorization. 7. The method as recited in claim 1, wherein probability of occurrence variables of a target entity's anticipated actions or the actions of other entities or natural events that would impact a target entity are assigned to each potential action and which variables comprise one or more of the additional information and variables unique to the analysis of actions. 8. The method as recited in claim 1, wherein the actions of a target entity, natural events and the actions of other entities are assigned a variable to identify the priority of the information about the action and a method to change the priority variable and which variables comprise one or more of the additional information and variables unique to the analysis of actions. 9. The method as recited in claim 1, wherein specific meta data is assigned to each action that defines a structure of the relationship of actions to one another and wherein relationship variables are assigned and which variables comprise some of the additional information and variables unique to the analysis of actions. 10. The method as recited in claim 1, wherein input data sets of actions are compared to expected actions and variance variables are determined and stored with action information and which variables comprise one or more additional information attributes and variables unique to the algorithmic analysis of anticipated actions. 11. The method as recited in claim 1, wherein specific meta data is assigned to each variance that defines a structure of the relationship of variances to one another and wherein relationship variables are assigned and which variables comprise some but not all of the additional information and variables unique to the analysis of anticipated actions. 12. The method as recited in claim 1, wherein the relationship of variances between actual actions and anticipated actions of a target entity, natural events and the anticipated actions of other entities are assigned a variable to identify the priority of the information about the relationship of variances and a method to change the priority variable and which variable comprises one or more of the additional information and variables unique to the analysis of anticipated actions. 13. The method as recited in claim 1, wherein a volatility variable of a target entity's actions or the actions of other entities or natural events that would impact a target entity are assigned to each action and which variable comprises one or more of the additional information and variables unique to the analysis of anticipated actions. 14. The method as recited in claim 1, wherein an action is categorized into one or more categories and which categories comprise one or more of the additional information and variables unique to the analysis of actions. 15. The method as recited in claim 1, wherein an action's categories are assigned one or more variables to identify the priority of the information about the category and a method to change the priority variables and which variables comprise one or more of the additional information and variables unique to the analysis of actions. 16. The method as recited in claim 1, wherein an action's categories are assigned one or more variables to identify the relationship between categories and a method to analyze the relationship between categories. 17. A system, comprising: a data warehouse configured to store variables and information related to a target entity's actions, the actions of other entities that would impact the target entity and natural event information that would impact the target entity; and a computer system configured to access said action variables and information stored on said data warehouse, wherein said computer system is further configured to: determine and assign one or more categories to a target entity's current actions or natural event and its priority based on a comparison of stored actions, events, categories, category relationships and to identify and store any variance between the meta data, variables or information about the action and current stored information of actions as variables and information. 18. The system as recited in claim 17, wherein said computer system determining the category, priority and variance to stored actions or events, analyzes the action or event, the action of other entities and other natural event information to anticipate the next action of the target entity or natural event and calculate one or more priority variables of that action. 19. The system as recited in claim 17, wherein said computer system stores information of new actions by the target entity, by other entities whose actions would impact the target entity, natural event information or other system supplied information with additional meta information and variables unique to the analysis of actions as performed by the system. 20. The system as recited in claim 17, wherein said computer system determines a level of volatility and velocity in the actions of the target entity or the actions of others or natural events or systems that would impact the target entity or natural event and which the system uses such information to calculate one or more priority variables assigned to the next action or event. 21. The system as recited in claim 17, wherein said computer system analyzes the information about a target entity's actions, the actions of other entities that would impact the target entity, natural event information and information supplied by other systems and the relationship between such actions and events to determine the next action of the target entity. 22. The system as recited in claim 17, wherein said computer system changes the category or categories or priority of a target entity's current actions or natural event based on an analysis of new actions performed by the target entity, by other entities whose actions would impact the target entity, natural event information or other system supplied information. 23. The system as recited in claim 17, wherein said computer system sends an indication to other systems regarding the priority and information about a target entity's next action or actions or natural events. 24. The system as recited in claim 17, wherein said computer system stores information about the variance between a target entity's current action or natural event and the anticipated action or actions or events for use in the analysis of future actions. 25. A computer-accessible medium comprising program instructions, wherein the program instructions are computer-executable to: determine the category and priority of the current action of a target entity or natural event, to store information about the current action or natural event and the variance to similar action or event information in a stored database, to analyze and determine the velocity and volatility of the target entity's action or natural event to stored known action or event information, to identify the next anticipated action or event options, to identify the next anticipated action or event with the highest probability of occurrence and to formulate an indication of such next action for use by other systems. 26. The computer-accessible medium as recited in claim 25, wherein determining the category and priority of the target entity's action and the actions of other entities that would impact the target entity, natural event information or information from other systems that comprises determining elements and variables that represent elements such as, but not limited to, movement, location, velocity, direction, data, color, pressure, proximity and type of nearby objects, input sensor information about the target entity actions and environment and comparing such information against a database of known information and identifying any variance to such information and using such information to set category and priority variables for the action. 27. The computer-accessible medium as recited in claim 25, wherein storing the category and priority of said target entity actions and the actions of other entities that would impact the target entity, natural event information or information from other systems, that comprises storing elements and variables that represent elements such as, but not limited to, movement, location, velocity, trajectory, direction, data, color, pressure, proximity and type of nearby objects, input sensor information, about the target entity actions and comparing such information against a database of known information and storing any variance to such information and using such stored information to set and store a new category and priority for subsequent actions. 28. The computer-accessible medium as recited in claim 25, wherein analyzing action or event variables comprises determining the status or state of a target entity's current action or natural event. 29. The computer-accessible medium as recited in claim 25, wherein analyzing action or event variables comprises determining the velocity of the target entity's current action or natural event to determine and store current velocity variables. 30. The computer-accessible medium as recited in claim 25, wherein analyzing action or event variables comprises determining the variance of the target entity's action or natural event to anticipated actions or events to determine and store a variance variables. 31. The computer-accessible medium as recited in claim 25, wherein analyzing action or event variables comprises determining the risk probability of the target entity's action or natural event and to determine and store risk probability variables. 32. The computer-accessible medium as recited in claim 25, wherein determining action or event variables comprises determining the risk probability variables of the target entity's action or natural event. 33. The computer-accessible medium as recited in claim 25, wherein determining the target entity's next anticipated action, actions or events comprises determining the action option variables of the target entity's action, actions or natural event and to make such variables available to other systems and devices.