Autonomous computational processes (“agents”) representing application-specific domain entities are provided with application-independent methods and data structures to monitor one or more streams of behavioral indicator data observed in their respective entities and detect and report the presence of application-defined patterns of satisfied constraints (signatures) in real time. The invention specifies two agent populations, one (“Host Agents”) representing each domain entity with a dedicated agent that maintains current signature detection probabilities (and their constraint components), the other (“Indicator Agents”) continuously monitoring the behavioral indicator data and updating constraint satisfaction and signature detection probabilities.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A method of continuously monitoring a stream of values of various application-specific behavioral indicators of domain entities and detecting the occurrence of application-defined patterns (signatures) in the entity behavior in a distributed and decentralized computational or physical environment, comprising the steps of: associating application-specific domain entities as producers of values of behavioral indicators with autonomous software Host Agents, each Host Agent being operative to perform independent processes, the processes including a Knowledge Management process and an Arrangement Process; associating application-specific signatures to be detected with one or more constraints defined on the value of a specific indicator, where the probability of detection of the signature is a function of the probability of satisfaction of each indicator constraint in that signature; associating each indicator constraint of each signature with one or more autonomous software Indicator Agents, each Indicator Agent being operative to perform independent processes, the processes including a Movement Decision process and a Host Agent Interaction Process; and continuously and repeatedly executing the processes by the agents to maintain up-to-date probability estimates for the presence of specific signatures in the behavior of domain entities in accordance with the requirements of an application. 2. The method of claim 1, including the step of adding or removing Host Agents from the application as their corresponding application-specific domain entities are added to or removed from the application. 3. The method of claim 1, wherein the domain entities produce the behavioral indicator data and communicate the data stream to their respective Host Agent in the application. 4. The method of claim 1, wherein the domain entities are observed by a separate set of sensors that produce the behavioral indicator data and communicate the data stream to the respective Host Agent in the application. 5. The method of claim 1, including the step of assigning each Host Agent and each Indicator Agent a position in an application-specific topology. 6. The method of claim 1, wherein the Host and Indicator Agents have positions in the topology, the method including the step of enabling agents to manipulate their position. 7. The method of claim 5, wherein each Host Agent is able to estimate the distance between its position in the topology relative to another given position value. 8. The method of claim 1, wherein each Host Agent maintains a data structure, comprising, at a minimum, the following values: (a) a numerical “priority” value for each behavioral indicator of the Host Agent, (b) a numerical “urgency” value for each behavioral indicator of the Host Agent, (c) a data structure for specific application-specific signatures, comprising of the following values: (i) the unique identifier of the signature (ii) the detection probability value of the signature (iii) a satisfaction probability value for each indicator constraint of the signature 9. The method of claim 1, wherein a Host Agent is operative to perform the Knowledge Management process using the following steps: (a) for each indicator, add the current priority value to the current urgency value and set the result as the new urgency value; (b) for each indicator constraint in each signature data structure, multiply its current satisfaction probability with a numerical “decay” factor in the (0,1) interval and set the resulting value as the new satisfaction probability; (c) for each indicator constraint in each signature data structure, remove the satisfaction probability from the data structure if its value is below an application-defined threshold; (d) for each signature data structure, compute the product of all satisfaction probability values and set the resulting value as the signature's detection probability; (e) for each signature data structure, remove the signature data structure if its detection probability value is below an application-defined threshold; and (f) for each indicator, set the priority value to the sum of an application-defined base value and the satisfaction probability of that indicator in each signature data structure. 10. The method of claim 1, wherein a Host Agent “A” is operative to perform the Arrangement process using the following steps: (a) enumerate all other Host Agents {h1, . . . , hn} whose topology-defined distance to the position of A is below an application-defined threshold; (b) for each such Host Agent compute an application-specific similarity measure si between current values of behavioral indicators in hi and A; and (c) utilizing the specific movement methods defined by the application-specific topology that defines A's position, reduce the topology-specific distance of A to hi with a high si value while increasing the topology-specific distance of A to hj with a low si value. 11. The method of claim 1, wherein an Indicator Agent “A” is operative to perform the Movement Decision process in the following steps: (a) enumerate all Host Agents {h1, . . . , hn} whose topology-defined distance to the position of A is below an application-defined threshold; (b) for each such Host Agent consider the current urgency value ui for the specific indicator assessed by A; and (c) utilizing the specific movement methods defined by the application-specific topology that defines A's position, reduce the topology-specific distance of A to hi with a high ui. 12. The method of claim 1, wherein an Indicator Agent “A” is operative to perform the Host Agent Interaction process in the following steps: (a) enumerate all Host Agents {h1, . . . , hn} whose topology-defined distance to the position of A is below an application-defined threshold; (b) for each such Host Agent hi, compute a probability pi to interact as the application-specific combination various values, including, but not limited to, hi's urgency value for A's indicator, hi's signature detection probability for A's signature, hi's indicator constraint satisfaction probability for A's signature and indicator, and the time since the last interaction of A with hi. (c) using an application-specific selection function that determines whether and which Host Agent hi to interact with, perform the following steps on hi: (i) taking the urgency value of hi for A's indicator, multiply it with a numerical “decay” factor in the (0,1) interval and set the resulting value as the new urgency; (ii) apply A's signature constraint to the behavioral indicator values of hi and any additional Host Agents with a distance to hi below an application-defined threshold and combine the resulting outcomes of the constraint application(s) into a new constraint satisfaction probability value S; (iii) if A's signature has no corresponding data structure in hi, create one; and (iv) for A's signature's data structure in hi, set A's indicator's satisfaction probability to S. 13. A method of claim 1, wherein Host Agents report their domain entity's identity and any signatures with a detection probability value above an application-defined threshold in accordance with the requirements of the application. 14. The method of claim 1, including signatures that represent abnormal behavior of a human or a machine. 15. The method of claim 1, including signatures that represent high or low utilization of a device or a machine. 16. The method of claim 1, wherein the behavioral indicators include measurements or activity reports. 17. The method of claim 1, wherein the application-specific domain entities include humans or machines.