Abstract: A system may include a memory and a processor in communication with the memory. The processor may be configured to perform operations. The operations may include receiving data and generating a contextual execution dependency graph with said data. The operations may include producing agents with said data and calculating an agent sequence for said agents based at least in part on said contextual execution dependency graph. The operations may include executing an automation script using said agent sequence and said contextual execution dependency graph.

Abstract: A method of designing a fire detection system comprising: determining a probability of a fire in a room; determining a number of fire detection devices for a fire detection system within the room in response to the probability of the fire in the room; determining a number of fire suppression devices for the fire detection system within the room in response to the probability of a fire in the room; and determining a location of each of the fire detection devices within the room and a location of the fire suppression devices within the room.

Abstract: Methods and systems for process analysis include determining attributes of an event log relating to a process. Attributes of an end task of the process are determined based on a comparison of a vector representation of the end task to vector representations to a set of criteria relating to process representations. Hyper-parameters of process mining models are tuned based on the attributes of the event log and the attributes of the end task. The process mining models are ranked based on the attributes of the event log and the attributes of the end task. The event log is mined using a top-ranked process mining model to generate a process representation. An inefficiency of the process is identified based on the process representation. The inefficiency is automatically corrected.

Abstract: A method, computer system, and a computer program product for generating a conversational bot for an application programming interface (API) is provided. The present invention may include parsing an API schema. The present invention may include generating sentences for the conversational bot from the parsed API schema. The present invention may include constructing the conversational bot by training a deep learning model. The present invention may include receiving a natural language expression from a user. The present invention may include determining whether the natural language expression is enough to activate the bot.

Abstract: An example operation may include one or more of tuning a language model based on dependencies between an original data set and a paraphrase data set of the original data set, parsing and annotating the paraphrase dataset with entity identifiers of predefined entities to generate an annotated paraphrase dataset, additionally tuning the language model based on entity dependencies between the original data set and the paraphrase data set based on the annotated paraphrase dataset, and storing the additionally tuned language model in a storage device.

Abstract: A method of determining a probability of a fire within one or more rooms of a building comprising: determining a geometry of a room in response to a floor plan: determining whether one or more articles are located within the room and a flammability of each of the one or more articles: determining whether one or more hazards are located within the room: and determining a probability of a fire in the room in response to at least one or more articles are located within the room, the flammability of each of the one or more articles, and the one or more hazards are located within the room.

Abstract: A computer-implemented method includes publishing a prediction task and KPI information. The method further includes receiving, at a certain time, a plurality of prediction results, each of the plurality of prediction results being produced by one of a plurality of participants with one of a private model and private data association with the one of the plurality of participants. The method further includes calculating, for each of the plurality of participants, a trade score based on the KPI information and the plurality of prediction results for each of the plurality of participants. The method further includes determining an acquirement score for the one of the private model and the private data associated with each of the plurality of participants using the corresponding trade score. The method further includes publishing the acquirement score for trading the one of the private model and the private data among the plurality of participants.

Abstract: Mechanisms are provided for forecasting information technology (IT) and environmental impacts on key performance indicators (KPIs). Machine learning (ML) computer model(s) are trained on historical data representing IT events and KPIs of organizational processes (OPs). The ML computer model(s) forecast IT events given KPIs, or KPI impact given IT events. Correlation graph data structure(s) are generated that map at least one of IT events to IT computing resources, or KPI impacts to OPs. The trained ML computer model(s) process input data to generate a forecast output that specifies at least one of a forecasted IT event or a KPI impact. The forecasted output is correlated with at least one of IT computing resource(s) or OP(s), at least by applying the correlation graph data structure(s) to the forecast output to generate a correlation output. A remedial action recommendation is generated based on the forecast output and correlation output.

Abstract: Mechanisms are provided for generating, executing, orchestrating, and monitoring an information technology (IT) incident remediation task workflow. An IT incident notification is received and a knowledge data structure associated with an IT resource corresponding to the IT incident is retrieved. IT remediation task(s) are extracted from the knowledge data structure and correlated with skills in a plurality of predetermined skills. Automated tools are correlated with corresponding skills in the plurality of predetermined skills. An IT incident remediation task workflow is generated based on a matching of skills associated with the IT remediation tasks and automation tools. The generated IT incident remediation task workflow is automatically executed on the at least one IT resource.

Abstract: Mechanisms are provided for forecasting information technology (IT) and environmental impacts on key performance indicators (KPIs). Machine learning (ML) computer model(s) are trained on historical data representing IT events and KPIs of organizational processes (OPs). The ML computer model(s) forecast IT events given KPIs, or KPI impact given IT events. Correlation graph data structure(s) are generated that map at least one of IT events to IT computing resources, or KPI impacts to OPs. The trained ML computer model(s) process input data to generate a forecast output that specifies at least one of a forecasted IT event or a KPI impact. The forecasted output is correlated with at least one of IT computing resource(s) or OP(s), at least by applying the correlation graph data structure(s) to the forecast output to generate a correlation output. A remedial action recommendation is generated based on the forecast output and correlation output.

Abstract: One embodiment provides a method, including: receiving a ranked listing of a plurality of candidates; within a first one of a plurality of collaboration rounds: (i) aggregating the ranked listings into an overall listing, (ii) presenting the overall listing to a first one of the job candidate matching agents, and (iii) receiving at least one modification to the overall listing from the agents; (iv) presenting a version of the overall listing to each of the remaining agents; and (v) receiving any modifications from the agents until all of the agents have had a turn; conducting others of the plurality of collaboration rounds: (i) presenting a version of the overall listing and (ii) receiving any modifications from the agents; (iii) presenting a version of the overall listing to each of the remaining agents, and (iv) receiving any modifications from the agents; and providing the final version to a user.

Abstract: A system may include a memory and a processor in communication with the memory. The processor may be configured to perform operations. The operations may include receiving data and generating a contextual execution dependency graph with said data. The operations may include producing agents with said data and calculating an agent sequence for said agents based at least in part on said contextual execution dependency graph. The operations may include executing an automation script using said agent sequence and said contextual execution dependency graph.

Abstract: A method of determining placement of nozzles within a fire suppression system comprising: determining a geometry of a room in response to a floor plan; determining a type of fire suppression agent required in response to at least one of articles in the room and hazards in the room; determining an amount of fire suppression agent required in response to at least one of the articles in the room, hazards in the room, the geometry of the room, average temperature in the room, and average pressure within the room; and determining a number of nozzles, a type of each of the nozzles, a location of each of the nozzles within the room in response to at least the amount of fire suppression agent required.

Abstract: A method of designing a fire suppression system including: determining nozzle placement for nozzles of a fire suppression system within a location; determining piping placement for pipes of the fire suppression system within the location; determining whether the nozzle placement or piping placement violate a constraint; and generating a map displaying the nozzle placement and the piping placement on a computing device.

Abstract: Methods, systems, and computer program products for adjusting machine learning models based on simulated fairness impact are provided herein. A computer-implemented method includes obtaining, by a central simulation system, policies to be used for performing a simulation involving machine learning models, implemented on different systems, interacting with a target population; providing information for configuring simulators on the different systems, each simulator representing at least the machine learning model of a given one of the different systems; performing iterations of the simulation for the policies, wherein, for each iteration, the central simulation system: predicts a state of the target population, provides the state to the simulators, and collects metrics based on results of the simulators; and selecting and sending one of the policies to at least one of the different systems based on the collected metrics.

Abstract: A method, computer system, and a computer program product for generating a conversational bot for an application programming interface (API)is provided. The present invention may include parsing an API schema. The present invention may include generating sentences for the conversational bot from the parsed API schema. The present invention may include constructing the conversational bot by training a deep learning model. The present invention may include receiving a natural language expression from a user. The present invention may include determining whether the natural language expression is enough to activate the bot.

Abstract: A system, method, and computer program product for implementing automated digital agent communication and control is provided. The method includes retrieving from a digital agent, a query associated with knowledge based control process. Digital knowledge elements, associated digital skills, and a sequence of control operations are received to obtain a response to the query. A first possible set of knowledge of a set of digital knowledge elements, skills, and an associated sequence of operation are selected and the first possible set of knowledge, skills, and associated sequence of operation are transmitted to the digital agent. A sequence of skills are executed with respect to digital knowledge elements and components and a hardware interface device is enabled to interact with and control various devices for enabling operational functionality associated with devices. Knowledge based fabric code associated with future instances of enabling the hardware interface device is updated.

Abstract: A building management system is provided. The building management system includes one or more variable air volume units and a controller. The controller includes a processor and a memory. The memory stores processor executable instruction. The processor executable instruction when executed by the processor cause the building management system to perform functional tests on the one or more variable air volume units of the building management system to generate building data; analyze the building data to produce health information per functional test; and visualize a condition of the building system based on the health information.

Abstract: A method and a system for agitation detection and response for a programming language are provided. The method includes collecting software code and activity data pertaining to one or more activities performed by a developer that is using a segment of a programming language. The method also includes evaluating the activity data to generate an agitation level of the developer when using the segment of the programming language. The method can also include generating a developer context by evaluating the software code. The developer context can include insights into the operation of features in the programming language by the developer. The activity and developer context can be provided to a software development provider for independent analysis.

Abstract: A method of designing a fire detection system including: determining a location of one or more fire detection devices within the building; and generating a map that displays the location of one or more fire detection device.