Abstract: In various examples, the present system tracks gameplay timeframes for when a user is engaged in an instance of gameplay. The system can then determine one or more typical timeframe(s) for when the user engages in gameplay. In some embodiments, the user can access a team matching UI and request to be matched with other user accounts and/or to be presented with a list of other user accounts who might be a good match for the user, such as those associated with similar typical timeframes for gameplay. Based on the request from the user, a set of user accounts available to be matched can be ranked based, at least in part, on a similarity between gameplay timeframes associated with the user and each of the user accounts in the set of user accounts. Using the ranking, the system can generate a team of users with similar typical gameplay timeframes.

Abstract: In various examples, the present system tracks gameplay timeframes for when a user is engaged in an instance of gameplay. The system can then determine one or more typical timeframe(s) for when the user engages in gameplay. In some embodiments, the user can access a team matching UI and request to be matched with other user accounts and/or to be presented with a list of other user accounts who might be a good match for the user, such as those associated with similar typical timeframes for gameplay. Based on the request from the user, a set of user accounts available to be matched can be ranked based, at least in part, on a similarity between gameplay timeframes associated with the user and each of the user accounts in the set of user accounts. Using the ranking, the system can generate a team of users with similar typical gameplay timeframes.

Abstract: Methods and apparatuses are provided to automatically identify overstated perpetual inventory (PI) conditions regarding an inventory level of an item in a retail space. For example, in some embodiments, a method performed by a control circuit comprises determining (504) that, a plurality of times, an item for sale at a retail store sells within a defined tolerance of a non-zero inventory quantity value and then stops selling for a period of time; and making (506) a determination that an overstated PI condition exists with respect to an inventory level of the item at the retail store. In some embodiments, the overstated PI condition is automatically quantified and may be automatically corrected.

Abstract: In some embodiments, apparatuses and methods are provided herein useful to forecasting product demand. In some embodiments, a system comprise a forecasting control circuit to: apply each of a plurality of different models to forecast demand of a first product over a first historic period generating historic forecasted demands of the first product, wherein at least a first model uses selected one or more variables that are predicted to have an uncharacteristic effect on predicted demand; select one of the models and apply the model in generating a forecasted future demand, wherein the selection of the model is based on a difference between each of the generated historic forecasted demands and actual sales; and identify actions to modify inventory of the first product at the first shopping facility based on the forecasted future demand.

Abstract: Methods and apparatuses are provided to automatically identify overstated perpetual inventory (PI) conditions regarding an inventory level of an item in a retail space. For example, in some embodiments, a method performed by a control circuit comprises determining (504) that, a plurality of times, an item for sale at a retail store sells within a defined tolerance of a non-zero inventory quantity value and then stops selling for a period of time; and making (506) a determination that an overstated PI condition exists with respect to an inventory level of the item at the retail store. In some embodiments, the overstated PI condition is automatically quantified and may be automatically corrected.

Abstract: Methods and apparatuses are provided to automatically identify overstated perpetual inventory (PI) conditions regarding an inventory level of an item in a retail space. For example, in some embodiments, a method performed by a control circuit comprises determining (504) that, a plurality of times, an item for sale at a retail store sells within a defined tolerance of a non-zero inventory quantity value and then stops selling for a period of time; and making (506) a determination that an overstated PI condition exists with respect to an inventory level of the item at the retail store. In some embodiments, the overstated PI condition is automatically quantified and may be automatically corrected.

Abstract: Methods and apparatuses are provided to automatically identify overstated perpetual inventory (PI) conditions regarding an inventory level of an item in a retail space. For example, in some embodiments, a method performed by a control circuit comprises determining (504) that, a plurality of times, an item for sale at a retail store sells within a defined tolerance of a non-zero inventory quantity value and then stops selling for a period of time; and making (506) a determination that an overstated PI condition exists with respect to an inventory level of the item at the retail store. In some embodiments, the overstated PI condition is automatically quantified and may be automatically corrected.

Abstract: In some embodiments, apparatuses and methods are provided herein useful to forecasting product demand. In some embodiments, a system comprise a forecasting control circuit to: apply each of a plurality of different models to forecast demand of a first product over a first historic period generating historic forecasted demands of the first product, wherein at least a first model uses selected one or more variables that are predicted to have an uncharacteristic effect on predicted demand; select one of the models and apply the model in generating a forecasted future demand, wherein the selection of the model is based on a difference between each of the generated historic forecasted demands and actual sales; and identify actions to modify inventory of the first product at the first shopping facility based on the forecasted future demand.

Abstract: Enforcing network service level agreements in a network infrastructure element comprises receiving, at the network infrastructure element, an application-layer message comprising one or more of the packets; forwarding the application-layer message toward a destination endpoint and concurrently copying the application-layer message without disrupting the forwarding; using the copied application-layer message, discovering one or more applications or services that are using the network; using the copied application-layer message, identifying one or more network-layer condition metrics, and identifying one or more application-layer condition metrics; determining, based on the identified network-layer condition metrics and the application-layer condition metrics, whether one or more conditions of a service level agreement are violated; and in response to determining a violation, performing one or more responsive operations on one or more network elements.

Abstract: A network element such as a router or switch provides application-level quality of service for application-layer messages processed in the network element, using application QoS logic which when executed by the one or more processors is operable to cause receiving an application-layer message; matching one or more attributes of the application-layer message to the message classification rules; determining a message classification of the application-layer message based on the matching; selecting one of the network-level QoS values using the mapping and based on the determined message classification; and marking a network-level header of the application-layer message using the selected QoS value. As a result, attributes of application messages at OSI Layer 5, 6, or 7 can be used to determine how to mark packets of the messages with QoS values at OSI Layer 2, 3 or 4, integrating application-level concepts of order and priority into network-layer QoS mechanisms.

Abstract: Enforcing network service level agreements in a network infrastructure element comprises receiving, at the network infrastructure element, an application-layer message comprising one or more of the packets; forwarding the application-layer message toward a destination endpoint and concurrently copying the application-layer message without disrupting the forwarding; using the copied application-layer message, discovering one or more applications or services that are using the network; using the copied application-layer message, identifying one or more network-layer condition metrics, and identifying one or more application-layer condition metrics; determining, based on the identified network-layer condition metrics and the application-layer condition metrics, whether one or more conditions of a service level agreement are violated; and in response to determining a violation, performing one or more responsive operations on one or more network elements.

Abstract: A network element such as a router or switch provides application-level quality of service for application-layer messages processed in the network element, using application QoS logic which when executed by the one or more processors is operable to cause receiving an application-layer message; matching one or more attributes of the application-layer message to the message classification rules; determining a message classification of the application-layer message based on the matching; selecting one of the network-level QoS values using the mapping and based on the determined message classification; and marking a network-level header of the application-layer message using the selected QoS value. As a result, attributes of application messages at OSI Layer 5, 6, or 7 can be used to determine how to mark packets of the messages with QoS values at OSI Layer 2, 3 or 4, integrating application-level concepts of order and priority into network-layer QoS mechanisms.

Abstract: Disclosed is an architecture for an intelligent agent and for a distributed platform for supporting many of such agents. Also described are scenarios wherein intelligent agents may be used.