Open interface management of virtual agent nodes

Cognitive software and/or machine learning software are monitored in a cognitive computing environment. Open interface management of virtual agent nodes is performed in the cognitive computing environment.

BACKGROUND

The present invention relates to management of deployed software-based cognitive virtual assistants/agents. More particularly, the present invention relates to open interface management of virtual agent nodes.

Virtual agent nodes are software entities that are installed on a variety of devices, such as cellular telephones and other devices. Virtual agent nodes are designed to interact with human users of those devices to assist the users with answers related to use of the devices, service plans available for use of the devices, or other forms of information.

SUMMARY

A computer-implemented method includes, by at least one processor(s) set, monitoring cognitive software and/or machine learning software in a cognitive computing environment; and performing open interface management of virtual agent nodes in the cognitive computing environment.

A system that performs the computer-implemented method and a computer program product that causes a computer to perform the computer-implemented method are also described.

DETAILED DESCRIPTION

The subject matter described herein provides open interface management of virtual agent nodes. Virtual agent nodes are alternatively termed “virtual agents,” “virtual assistants,” or “VAs” herein for ease of reference. Virtual agents are “cognitive entities (CEs)” by design, and as designed are software entities based upon “cognitive models” enabled by use of Big Data platforms. The subject matter described herein provides an open interface that is standardized for management of virtual agents across a variety of installation platforms and patterns, as further described below. In certain implementations, the technology described herein extends and enhances conventional simple network management protocol (SNMP) to provide new “cognitive” management features and capabilities that allow remote control and management of deployed cognitive virtual agents. However, it should be understood that any management protocol that implements the technical details described herein may be utilized as appropriate for a given implementation. When implemented using SNMP as a protocol foundation, the cognitive technological enhancements to SNMP and the resulting protocol described herein are termed “cognitive SNMP” (C-SNMP). When any other protocol is utilized or cognitive management is referred to more broadly, the technology described herein is termed a “cognitive management protocol.”

As cognitive entities within a rapidly-emerging area of computing technology, virtual agents are designed to remember the past, to interact with humans, to continuously learn from these interactions, and to refine their responses for future interactions according to what they learn from previous interactions. Virtual agents are further designed to interact verbally with a device user through automated voice generation and voice recognition technologies to assist a device user with use of the device, with searching for information, and with other forms of helpful tasks. The present technology solves several recognized virtual agent management problems described in more detail below by providing a new form of virtual agent communication interface/protocol that improves remote monitoring and management of virtual agents that are deployed within complex and distributed computing platforms.

It should be noted that there is no standardized approach to deployment, interface/management interactions, upgrades, and other aspects of virtual agent nodes. As a result, a technical problem exists because each virtual agent node may have a different communication interface and command set. The technology described herein solves this technology problem. Specifically, the technology described herein provides technical features that improve interoperation of virtual agents and virtual agent management nodes by providing a standardized interface where standards did not previously exist. By implementation of the new interface standardization described herein, virtual agent nodes may be managed more effectively for deployment, interface/management interactions, upgrades, and a variety of other operations to which virtual agents may be deployed now or in the future.

Some terminology and deployment platform options used in describing some embodiments of the present technology will now be explained. The technology described herein may be implemented in a variety of management platforms. For example, an apparatus in blue stack platforms, such as IBM Tivoli Composite Application Manager (ITCAM) may be extended and enhanced to implement the technology described herein. Additionally, other network management tools may be extended and enhanced. The International Standardization Organization (ISO) model defines certain network management tasks termed fault, configuration, accounting, performance, and security (FCAPS). The technology described herein extends and enhances conventional FCAPS by adding “cognitive” aspects and control features to the ISO model. The added “cognitive” aspects are termed “cognitive management tasks” herein, and the resulting augmented ISO model is termed “C-FCAPS” herein. C-FCAPS enhances the conventional management categories of the ISO model-based network management tasks to add cognitive management tasks for remote management and control of deployed virtual agents. A new form of management entity, termed a “C-FCAPS SNMP Manager” herein, may be deployed in multiple typed patterns (e.g., strongly-typed, federated, or consolidated patterns), and may perform an open-interface based management of deployed virtual agent nodes. These typed-pattern deployment solutions may be formed into a two-tier or a three-tier model, with the deployed virtual agents capturing the various parameters of the respective nodes within the respective tiered model(s). To obtain information and results of various cognitive management tasks, the C-FCAPS SNMP Managers may poll the deployed virtual agents, or the deployed virtual agents may send alarms, notifications, and other VA-initiated communications, hereinafter collectively termed “traps,” to report the information and results of various cognitive management tasks to the C-FCAPS SNMP Managers.

The technology described herein operates by monitoring cognitive software and/or machine learning software in a cognitive computing environment, and performing open interface management of virtual agent nodes in the cognitive computing environment

It should be noted that conception of the present subject matter resulted from recognition of certain limitations associated with remote management of virtual agents as remote executing software components. For example, it was observed that virtual agents are being deployed in continually-increasing numbers on mobile devices, such as smart phones and on other types of devices/platforms, to perform increasing varieties of tasks. Additionally, virtual agents may be deployed through federated or other patterns. However, it was determined that there is no unified monitoring or management solution across so many platforms and installations that may be leveraged. As such, the increasing numbers of deployed virtual agents and the complexities associated with virtual agent management across this variety of deployment patterns and platforms has resulted in a virtual agent management problem because there is no standardized technology by which to monitor and tune performance of these deployed virtual agents across so many different technologies. Specifically, it was observed that it has become technically difficult to: (i) manage deployed virtual agents to provide/adjust configuration(s), (ii) to interact remotely with deployed virtual agents, (iii) to query information and configuration information from deployed virtual agents, and (vi) to tune performance of deployed virtual agents as remote executing software components. As a result, it was determined that there is a technological need to provide an open-interface enabled management capability for remote virtual agents across these different typed deployment patterns and platforms. It was further observed that in traditional network management, such as within the telecommunications industry, management/monitoring of network equipment (e.g., devices) is performed by use of Simple Network Management Protocol (SNMP). However, it was determined that this conventional technology is not designed for management of cognitive-specific capabilities of deployed software-based virtual agents. The present subject matter improves remote virtual agent management by extending the open interface provided by SNMP to facilitate remote management of virtual/cognitive software agents and by providing a new form of “cognitive” SNMP-based management of virtual agents (VAs), as described above and in more detail below. As such, improved deployment and ongoing management of virtual agents may be obtained through use of the present technology.

As introduced above, SNMP is a standardized communication protocol that was designed and conventionally used to remotely control and monitor devices, such as telecommunications devices. SNMP defines messaging operations that may be performed from a controlling device to set (“put”) or retrieve (“get”) various device parameters and/or device configuration values of a remote device that is being controlled by the controlling device. The remote device may additionally initiate communications in the form of an alarm/trap to report information to the controlling device. The subject matter described herein extends SNMP into “cognitive SNMP” (C-SNMP), which is a new form of open interface management of virtual agent nodes in a cognitive computing environment. By use of C-SNMP, as described herein, cognitive software and/or machine learning software may be monitored, and open interface management of virtual agent nodes in a cognitive computing environment may be performed efficiently and effectively as a technological advancement in distributed cognitive computing.

As introduced above, the various typed deployment patterns within which virtual agents may be deployed include strongly-typed patterns, federated patterns, and consolidated patterns. In strongly-typed patterns, a virtual agent is centralized and is a point of contact for a set of nodes/devices. The C-FCAPS SNMP Manager directly interacts with the virtual agent and retrieves virtual agent object identifiers (VA-OIDs) based upon a configured polling frequency of the virtual agent(s), or the respective virtual agents may send traps to the C-FCAPS SNMP manager. In the federated pattern, the C-FCAPS SNMP manager interacts with multiple virtual agents, and thereby forms a virtual layer of virtual agents. In the consolidated pattern, the C-FCAPS SNMP manager creates a consolidated model of the virtual agents and performs the C-FCAPS function by use of the consolidated model to interact with the deployed virtual agents. Virtual agent object identifiers (VA-OIDs) and virtual agent management information bases (VA-MIBs) are each tree structures that organize the various parameters that are used to control and manage virtual agents, and will be described in more detail below after the following the system descriptions.

Accordingly, the subject matter described herein for open interface management of virtual agent nodes provides several technical advantages over conventional technologies. For example, the C-FCAPS SNMP manager provides and facilitates open interface-based monitoring and management of cognitive models for virtual agent nodes. The subject matter described provides a tiered architecture for monitoring and management of virtual agent nodes and management entities independently or in combination within any of the federated models, consolidated models, and strongly-typed models. The technology described herein provides object identifiers for cognitive parameters that are exposed to consuming information managers, such as for monitoring statistics, configuration, billing, and other features related to virtual nodes. The present technology is capable of guarding and abstracting both exposure and access of the virtual nodes through a security layer based on the respective consuming information managers to which the virtual agent nodes are exposed. Further, cognitive agents may be provided within a hierarchy of layered cognitive capabilities that are layered selectively as appropriate and varied for each particular implementation. As the implementations change over time, the hierarchy and layering of the cognitive capabilities may be adjusted to account for the respective changes. As such, the technology provides capabilities to form dynamic cognitive/virtual agent groups and assign dynamic cognitive virtual agent managers from distributed virtual agent nodes or layered cognitive capabilities, and these dynamic agent groups and managers may also be changed over time to accommodate changes in deployment architectures and features. Agents may be further assigned to collect parameters at their respective nodes and to provide those parameters to managing entities. Example parameters that may be collected for a particular node include, among other possible parameters, a number of utterances handled according to the defined specification (e.g., utterances per second, per minute, etc.); a number of utterances that resulted in flow through to another service/entity or to an alternative form of assistance (e.g., another cognitive entity, initiation of communication between the device user and technical support or customer service personnel, etc.); a number of utterances that resulted in successful responses (e.g., question answered, search completed, etc.); and/or, a number of utterances that resulted in unsuccessful responses (e.g., I don't know, etc.). The technology described herein provides cognitive capabilities for virtual agents to assert traps to the respective monitoring managers for bi-directional integration within the complex and dynamic deployment options described above. Accordingly, the technology described herein extends conventional SNMP standards to provide new technology for monitoring the Cognitive ecosystem, thus enabling the existing network management systems (NMS) with extended capability of service monitoring, which may reduce costs in addition to providing the technological advancements described herein.

The open interface management of virtual agent nodes described herein may be performed in real time to allow prompt management and reconfiguration/tuning of virtual agents. For purposes of the present description, real time shall include any time frame of sufficiently short duration as to provide reasonable response time for information processing acceptable to a user of the subject matter described. Additionally, the term “real time” shall include what is commonly termed “near real time”—generally meaning any time frame of sufficiently short duration as to provide reasonable response time for on-demand information processing acceptable to a user of the subject matter described (e.g., within a portion of a second or within a few seconds). These terms, while difficult to precisely define are well understood by those skilled in the art.

Additional detailed of the algorithmic processing and computational efficiencies will be provided further below. The following portion of the present description provides examples of advanced computational platform(s) within which the present technology may be implemented, followed by further details of the open interface management of virtual agent nodes described herein.

It should be noted that the present technology may be implemented within or as part of a cloud computing environment (e.g., for data analytics associated with management of deployed virtual agents), or may be implemented as a customized environment-specific solution. As such, examples of implementations for both environments are included herein. Additionally, the following examples illustrate several types of computing devices upon which virtual agents may be deployed and managed.

Characteristics are as follows:

Service Models are as follows:

Deployment Models are as follows:

Within the examples above, the cloud computing environment illustrates several types of computing devices54A-N upon which virtual agents may be deployed and managed. Regarding alternative platform implementation options,FIGS. 3 and 4below are directed to such alternatives. It should be understood that the various alternatives may be combined with or substituted with the implementation options described above and below, as appropriate for the given implementation.

FIG. 3is a block diagram of an example of an implementation of a system100for open interface management of virtual agent nodes. A computing device_1102through a computing device_N104communicate via a network106with several other devices. The other devices include a server_1108through a server_M110. The computing device_1102through the computing device_N104may each host a virtual agent for communications with a user of the respective computing device. Further, one or more of the server_1108through the server_M110may each operate as a C-FCAPS SNMP Manager that manages and controls the virtual agents deployed on the computing device_1102through the computing device_N104, as described above and in more detail below. As described above, the deployments of virtual agents within the system100may be provided within a hierarchy of layered cognitive capabilities that are layered selectively as appropriate and varied for each particular implementation. Further, the various deployment patterns within which virtual agents may be deployed include strongly-typed deployment patterns, federated deployment patterns, and consolidated deployment patterns. A database112represents one or more physical storage devices and may store configuration, management, and deployment information for use in control and management of virtual agent nodes by the respective server_1108through the server_M110.

As will be described in more detail below in association withFIG. 4throughFIG. 7, the server_1108through the server_M110may each provide automated open interface management of virtual agent nodes. The open interface management of virtual agent nodes is based upon standardized management of virtual agents across a variety of the deployment patterns described above.

In view of the implementation alternatives described above, the present technology may be implemented within a cloud computing platform, at a user computing device, at a server device level, or by a combination of such platforms and devices as appropriate for a given implementation. A variety of possibilities exist for implementation of the present subject matter, and all such possibilities are considered within the scope of the present subject matter.

The network106may include any form of interconnection suitable for the intended purpose, including a private or public network such as an intranet or the Internet, respectively, direct inter-module interconnection, dial-up, wireless, or any other interconnection mechanism capable of interconnecting the respective devices.

The server_1108through the server_M110may include any device capable of providing data for consumption by a device, such as the computing device_1102through the computing device_N104, via a network, such as the network106. As such, the server_1108through the server_M110may each include a web server, application server, or other data server device.

The database112may include a relational database, an object database, or any other storage type of device. As such, the database112may be implemented as appropriate for a given implementation.

FIG. 4is a block diagram of an example of an implementation of a core processing module200capable of performing processing associated with open interface management of virtual agent nodes. The core processing module200may be associated with either the computing device_1102through the computing device_N104or with the server_1108through the server_M110, or with devices within the cloud computing environment50, as appropriate for a given implementation. As such, the core processing module200is described generally herein, though it is understood that many variations on implementation of the components within the core processing module200are possible and all such variations are within the scope of the present subject matter. Further, the core processing module200may be implemented as an embedded processing device with circuitry designed specifically to perform the processing described herein as appropriate for a given implementation.

The core processing module200may provide different and complementary processing associated with open interface management of virtual agent nodes in association with each implementation. As such, for any of the examples below, it is understood that any aspect of functionality described with respect to any one device that is described in conjunction with another device (e.g., sends/sending, etc.) is to be understood to concurrently describe the functionality of the other respective device (e.g., receives/receiving, etc.).

A central processing unit (CPU)202(“processor” or “application-specific” processor) provides hardware that performs computer instruction execution, computation, and other capabilities within the core processing module200. A display204provides visual information to a user of the core processing module200and an input device206provides input capabilities for the user.

The display204may include any display device, such as a cathode ray tube (CRT), liquid crystal display (LCD), light emitting diode (LED), electronic ink displays, projection, touchscreen, or other display element or panel. The input device206may include a computer keyboard, a keypad, a mouse, a pen, a joystick, touchscreen, a microphone and voice command processing unit, or any other type of input device by which the user may interact with and respond to information on the display204.

A communication module208provides hardware, protocol stack processing, and interconnection capabilities that allow the core processing module200to communicate with other modules within the system100, or within the cloud computing environment50, as appropriate for a given implementation. The communication module208may include any electrical, protocol, and protocol conversion capabilities useable to provide interconnection capabilities, as appropriate for a given implementation. As such, the communication module208represents a communication device capable of carrying out communications with other devices. The communication module208may further include one or more wireless communication capabilities, as appropriate for the given implementation.

A memory210includes a virtual agent(s) storage area212that stores configuration information for one or more virtual agents within core processing module200. The virtual agent(s) configuration information may include deployment information, parameter configuration(s), collected parameter data, or other information, as appropriate for the given implementation. Further, the virtual agent(s) configuration information may be associated with one or more virtual agents that are either executing locally or deployed at different computing nodes, as appropriate for a given implementation.

A virtual agent execution area214provides execution space for one or more executing virtual agents. It is understood that other applications may be executed within the memory210.

It is further understood that the memory210may include any combination of volatile and non-volatile memory suitable for the intended purpose, distributed or localized as appropriate, and may include other memory segments not illustrated within the present example for ease of illustration purposes. For example, the memory210may include a code storage area, an operating system storage area, a code execution area, and a data area without departure from the scope of the present subject matter.

An open interface management module216is also illustrated. The open interface management module216provides virtual agent deployment and management capabilities for the core processing module200, as described above and in more detail below. As such, the open interface management module216implements the automated open interface management of virtual agent nodes of the core processing module200.

It should also be noted that the open interface management module216may form a portion of other circuitry described without departure from the scope of the present subject matter. The open interface management module216may form a portion of an interrupt service routine (ISR), a portion of an operating system, or a portion of an application without departure from the scope of the present subject matter. The open interface management module216may also include an embedded device with circuitry designed specifically to perform the processing described herein as appropriate for a given implementation.

The database112is again shown withinFIG. 4associated with the core processing module200. As such, the database112may be operatively coupled to the core processing module200without use of network connectivity, as appropriate for a given implementation.

The CPU202, the display204, the input device206, the communication module208, the memory210, the open interface management module216, and the database112are interconnected via an interconnection218. The interconnection218may include a system bus, a network, or any other interconnection capable of providing the respective components with suitable interconnection for the respective purpose.

Though the different modules illustrated withinFIG. 4are illustrated as component-level modules for ease of illustration and description purposes, it should be noted that these modules may include any hardware, programmed processor(s), and memory used to carry out the functions of the respective modules as described above and in more detail below. For example, the modules may include additional controller circuitry in the form of application specific integrated circuits (ASICs), processors, antennas, and/or discrete integrated circuits and components for performing communication and electrical control activities associated with the respective modules. Additionally, the modules may include interrupt-level, stack-level, and application-level modules as appropriate. Furthermore, the modules may include any memory components used for storage, execution, and data processing for performing processing activities associated with the respective modules. The modules may also form a portion of other circuitry described or may be combined without departure from the scope of the present subject matter.

Additionally, while the core processing module200is illustrated with and has certain components described, other modules and components may be associated with the core processing module200without departure from the scope of the present subject matter. Additionally, it should be noted that, while the core processing module200is described as a single device for ease of illustration purposes, the components within the core processing module200may be co-located or distributed and interconnected via a network without departure from the scope of the present subject matter. Many other possible arrangements for components of the core processing module200are possible and all are considered within the scope of the present subject matter. It should also be understood that, though the database112is illustrated as a separate component for purposes of example, the information stored within the database112may also/alternatively be stored within the memory210without departure from the scope of the present subject matter. Accordingly, the core processing module200may take many forms and may be associated with many platforms.

FIG. 5is a diagram of an example of an implementation of a virtual agent object identifier (VA-OID)500for locating and accessing virtual agents and their respective parameters to implement open interface management of virtual agent nodes. It should be noted that the VA-OID is extended and modified from the ISO variant of OIDs (e.g., beginning with a one “1” at its root), though it is understood that additional variants of OIDs exist and the technology described herein may be applied to any such variant. The VA-OID illustrated withinFIG. 5represents an extension of the OID structure that allows a C-FCAPS SNMP manager to reach an object/node in a virtual agent management information base (VA-MIB).

As can be seen inFIG. 5, element502collectively represents the first five dot-separated integers, namely 1.3.6.4.1, of the VA-OID500as a set. The element502represents standard ISO fields/values, where the first field/numeral “1” indicates this is an ISO OID, the second field/numeral “3” indicates organization, the third field/numeral “6” indicates the Department of Defense (DOD), the fourth field/numeral “1” indicates Internet, and the fifth field/numeral “4” indicates private. It is the remaining portions of the VA-OID to which the present subject matter pertains.

Specifically, remaining element504of the VA-OID500shows cognitive-specific SNMP augmentations/additions that are defined to implement the cognitive SNMP-based management of virtual agents (VAs) described herein. The first field/numeral in the element504indicates the cognitive service port (CS-PORT), alternatively termed the cognitive location of the respective virtual agent. The second field/numeral “Xx1” in the element504indicates the respective cognitive service identifier (CS-ID). The third field/numeral “yy1” in the element504selectively indicates node-specific cognitive service parameter identifiers (CS-P-IDs) of parameters made available by the respective virtual agent on the respective cognitive service port.

Example parameters of a virtual agent that may be collected and provided by access to the VA-OID500are: (i) number of frames of data created; (ii) number of utterances handled pursuant to the defined specification (e.g., per second, per minute, etc.); (iii) number of utterances that resulted in flow through by the virtual agent to another service/entity or to an alternative form of assistance (e.g., another cognitive entity, initiation of communication between the device user and technical support or customer service personnel, etc.); (iv) number of utterances that resulted in successful responses; and, (v) number of utterances that resulted in unsuccessful responses (e.g., virtual agent saying “I do not know that answer”). It should be noted that the above examples are provided as a foundation for implementation of the present technology for cognitive SNMP-based management of virtual agents (VAs). Many additional parameters of a given virtual agent may be defined and implemented according to the detailed description herein, as appropriate for a given virtual agent implementation, and all such parameters are considered within the scope of the present description.

FIG. 6throughFIG. 7described below represent example processes that may be executed by devices, such as the core processing module200, to perform the open interface management of virtual agent nodes associated with the present subject matter. Many other variations on the example processes are possible and all are considered within the scope of the present subject matter. The example processes may be performed by modules, such as the open interface management module216and/or executed by the CPU202, associated with such devices. It should be noted that time out procedures and other error control procedures are not illustrated within the example processes described below for ease of illustration purposes. However, it is understood that all such procedures are considered to be within the scope of the present subject matter. Further, the described processes may be combined, sequences of the processing described may be changed, and additional processing may be added or removed without departure from the scope of the present subject matter.

FIG. 6is a flow chart of an example of an implementation of a process600for open interface management of virtual agent nodes. The process600represents a computer-implemented method of performing the subject matter described herein. At block602, the process600monitors cognitive software and/or machine learning software in a cognitive computing environment. At block604, the process600performs open interface management of virtual agent nodes in the cognitive computing environment.

FIG. 7is a flow chart of an example of an implementation of a process700for open interface management of virtual agent nodes. The process700represents a computer-implemented method of performing the subject matter described herein. The process700further represents an example of processing that may be performed by one or more virtual agent managers within a variety of typed deployment patterns/architectures, as described above, to implement the cognitive fault, configuration, accounting, performance, and security (C-FCAPS) processing described herein. It should additionally be noted that virtual agents may be initially deployed as part of initial device functionality. Alternatively, virtual agents may be deployed and upgraded at any time. Accordingly, the following description addresses deployment and upgrade of virtual agent nodes separately. It should further be understood that all communications described below between a C-FCAPS manager that executes the process700and virtual agents may be performed using the cognitive SNMP (C-SNMP) described above. The following description begins with details of higher-level iterative processing to perform several different virtual agent management tasks, followed by details of individual branches of virtual agent management processing.

With respect to the higher-level iterative processing, at decision point702the process700makes a determination as to whether to deploy one or more virtual agents (VAs). In response to determining not to deploy one or more virtual agents (VAs), the process700makes a determination at decision point704as to whether to retrieve virtual agent information from one or more deployed virtual agents. In response to determining not to retrieve virtual agent information from one or more deployed virtual agents, the process700makes a determination at decision point706as to whether a virtual agent (VA) trap has been received from one or more deployed virtual agents. In response to determining that a virtual agent (VA) trap has not been received from one or more deployed virtual agents, the process700makes a determination at decision point708as to whether to upgrade any deployed virtual agents (VAs). In response to determining not to upgrade any deployed virtual agents (VAs), the process700makes a determination at decision point710as to whether to pattern deployed virtual agents, which may include initial typed pattern/architecture assignments or typed pattern/architectural changes to one or more sets of deployed virtual agents to assign and/or adjust hierarchical control relationships for open interface management of virtual agent nodes. In response to determining not to pattern deployed virtual agents, the process700returns to decision point702and iterates as described above to selectively process any of the open interface management tasks described above.

Returning to the description of decision point702, in response to determining to deploy one or more virtual agents (VAs), at block712the process700identifies one or more typed deployment patterns that are or that may be utilized to manage newly-deployed virtual agents. As described above, the typed deployment patterns may include strongly-typed patterns, federated patterns, and consolidated patterns, along with other typed deployment and virtual agent management patterns that may be identified as useful over time. At block714, the process700deploys one or more virtual agents to one or more target devices. Cognitive SNMP (C-SNMP) may be utilized to establish VA-OIDs for each parameter that is available for the given virtual agents that are being deployed, such that the respective virtual agents are functional on the respective devices to be queried for virtual agent information and parameters. At block716, the process700organizes the deployed virtual agent nodes according to one or more typed deployment patterns and associates the deployed virtual agents with assigned virtual agent (e.g., C-FCAPS) managers. It should be noted that deployed virtual agents may be organized initially within one typed pattern with a given virtual agent manager, and these associations may be changed at any time to re-architect management of deployed virtual agents. The process700returns to decision point704, and iterates as described above.

Returning to the description of decision point704, in response to determining to retrieve virtual agent information from one or more deployed virtual agents, at block718the process700polls one or more virtual agents using the C-SNMP protocol described above. The process700may specifically utilize the virtual agent object identifiers (VA-OIDs) and virtual agent management information bases (VA-MIBs) to query/poll the respective virtual agents. As described above, a VA-MIB may identify a hierarchy of deployed virtual agents and available parameters using VA-OIDs. The VA-OIDs specify the respective cognitive service port (CS-PORT), cognitive service identifiers (CS-ID), and node-specific cognitive service parameter identifiers (CS-P-IDs) of the respective virtual agents usable to access specific information associated with the respective virtual agents.

At block720, the process700processes the retrieved virtual agent information. Processing of the retrieved virtual agent information may include a variety of different types of processing. The processing at block720may include processing to determine virtual agent load information, effectiveness and interaction throughput, virtual agent feature usage, determinations regarding whether to upgrade particular virtual agent nodes, and other processing as appropriate for a given implementation. Further, and as described above, parameters of a virtual agent that may be collected and provided by access to the VA-OID are: (i) number of frames of data created; (ii) number of utterances handled pursuant to the defined specification (e.g., per second, per minute, etc.); (iii) number of utterances that resulted in flow through by the virtual agent to another service/entity or to an alternative form of assistance (e.g., another cognitive entity, initiate communication between the device user and technical support or customer service personnel, etc.); (iv) number of utterances that resulted in successful responses; and, (v) number of utterances that resulted in unsuccessful responses (e.g., virtual agent saying “I do not know that answer”). It should be noted that the above examples are provided as a foundation for implementation of the present technology for cognitive SNMP-based management of virtual agents (VAs). Many additional parameters of a given virtual agent may be defined and implemented according to the detailed description herein, as appropriate for a given virtual agent implementation, and all such parameters are considered within the scope of the present description. Any of these types and additional available parameters may be utilized and processed to make management decisions about deployed virtual agents. The process700returns to decision point706, and iterates as described above.

Returning to the description of decision point706, in response to determining that a virtual agent (VA) trap has been received from one or more deployed virtual agents, at block722the process700processes the received virtual agent trap. For purposes of the present description, processing of the received virtual agent trap may include cognitive processing of information transmitted by the respective deployed virtual agent. The processing of the virtual agent trap may further include determining whether to upgrade the particular virtual agent, whether to change configured/designed virtual agent processing, or other determinations as appropriate for a given implementation. The process700returns to decision point708, and iterates as described above.

Returning to the description of decision point708, in response to determining to upgrade any deployed virtual agents (VAs), at block724the process700upgrades the respective virtual agent using C-SNMP to identify the respective CS-PORT and CS-ID to upgrade. Upgrading of any deployed virtual agents (VAs) may further include coordination with the respective C-FCAPS managing node to assist with management of the virtual agent upgrade. The process700returns to decision point710, and iterates as described above.

Returning to the description of decision point710, in response to determining to pattern deployed virtual agents, at block726the process700determines one or more current virtual agent deployment pattern(s). As described above, virtual agents may be organized into a variety of typed patterns. The processing at block726evaluates current deployment pattern(s) for further evaluation of changes to the respective deployment pattern(s).

At block728, the process700identifies any appropriate deployment pattern changes. Deployment pattern changes may be based, for example, upon load of given sets of virtual agents and throughput capabilities of the respective C-FCAPS managing nodes. Any architectural changes that may improve efficiency may be identified and utilized to change one or more deployment patterns of one or more sets of virtual agents. At block730, the process700changes deployment patterns of any virtual agents for which changes have been identified. Changing deployment patterns may include combining and partitioning sets of virtual agents, and any other rearrangement or restructuring of virtual agent nodes appropriate for a given implementation. At block732, the process deploys and/or updates one or more virtual agents to inter-communicate according to the new/updated pattern architecture(s). As a result, any changes may be rapidly deployed to promptly improve operations and interactions for open interface management of virtual agent nodes. The process700returns to decision point702, and iterates as described above.

As such, the process700performs open interface management of virtual agent nodes using a variety of technical virtual agent deployment and management operations. The process700operates to deploy, query, process traps, upgrade, and change deployment patterns for virtual agent nodes. Many other variations on the example processing for open interface management of virtual agent nodes may be performed consistent with the description herein, and all such variations are considered to be within the scope of the present subject matter.

Some embodiments of the present invention may improve the technology of computers in one, or more, of the following ways: (i) improved processing capabilities for management of virtual agent nodes, (ii) improved consistency of processing for deployment and management of virtual agent nodes, (iii) improved control of deployment and deployment patterns and pattern changes for virtual agent node management, (iv) improved computing resource utilization for deployment and management of virtual agent nodes, (v) improved efficiency of computer-based communications for deployment and management of virtual agent nodes, and (vi) improved control of upgrades and feature enhancements for virtual agent nodes.

The present invention is not abstract because it relates particularly to computer operations and/or hardware that improve distributed computer processing and virtual agent computer-interface processing for reasons that may include the following: (i) improving real-time processing capabilities for management of virtual agent nodes, (ii) improving consistency of processing for deployment and management of virtual agent nodes, (iii) improving real-time control of deployment and deployment patterns and pattern changes for virtual agent node management, (iv) improving computing resource utilization for deployment and management of virtual agent nodes, (v) improving efficiency of real-time computer-based communications for deployment and management of virtual agent nodes, and (vi) improving real-time control of upgrades and feature enhancements for virtual agent nodes.

As described above in association withFIG. 1throughFIG. 7, the example systems and processes provide open interface management of virtual agent nodes. Many other variations and additional activities associated with open interface management of virtual agent nodes are possible and all are considered within the scope of the present subject matter.