Abstract: A computer-implemented system and method for training and deploying deep reinforcement learning (DRL) agents using neural program policies (NPPs) is disclosed. An NPP comprises a policy program authored in a domain-specific language (DSL) embedded in a general-purpose programming language, wherein the DSL defines procedural OBSERVE, ACT, REWARD, and DONE instructions that transform an open-structured partially observable Markov decision process (POMDP) into a structured, learnable DRL representation. An adaptive multiheaded recurrent neural network architecture reactively instantiates deep neural network (DNN) head models matched to dynamically encountered action space specifications and observation types, sharing a common fixed-size recurrent core. An autoregressive predictive model trained jointly with the policy serves as a surrogate model of the environment, enabling training at computational speeds orders of magnitude faster than direct environment simulation.

Abstract: Systems, methods and computer program products for automatically ingesting and filing documents in a database having a plurality of file locations. An electronic file having one or more documents is received. For each document in the received file, text data is identified and used to generate a plurality of suggested file locations for the received documents. Machine learning systems may be used to enhance the accuracy of suggested file locations.

Abstract: Systems, methods and computer program products for automatically ingesting and filing documents in a database having a plurality of file locations. An electronic file having one or more documents is received. For each document in the received file, text data is identified and used to generate a plurality of suggested file locations for the received documents. Machine learning systems may be used to enhance the accuracy of suggested file locations.

Abstract: Methods, systems and computer program products for organizing and displaying in real-time data related to a plurality of documents. A plurality of documents and a plurality of entity identifiers are stored in a relational database storage. Each entity identifier has an entity type selected from a plurality of entity types. A plurality of entity associations between the plurality of entity identifiers and the plurality of documents are stored in a non-relational database storage. Each entity association defines a relationship between one or more entity identifiers and a selected document in the plurality of documents. A plurality of file icons are displayed in a display interface. The plurality of file icons includes active icons corresponding to a selection of the plurality of documents where the selection is determined by querying the non-relational database storage using at least one currently-selected entity identifier.

Abstract: Methods and systems for sharing electronic documents are described herein. The example method includes storing the electronic documents in a relational database storage; storing entity identifiers in the relational database storage, each entity identifier representing an entity type; recording in a non-relational database storage associations between the electronic documents and at least one entity identifier, each association comprising a relationship between a set of electronic documents and the at least one entity identifier; associating a delegate account with the at least one entity identifier; and based on an association recorded in the non-relational database storage for the at least one entity identifier, granting the delegate account a subset of document management functions available for the set of documents.

Abstract: Methods and systems for sharing electronic documents are described herein. The example method includes storing the electronic documents in a relational database storage; storing entity identifiers in the relational database storage, each entity identifier representing an entity type; recording in a non-relational database storage associations between the electronic documents and at least one entity identifier, each association comprising a relationship between a set of electronic documents and the at least one entity identifier; associating a delegate account with the at least one entity identifier; and based on an association recorded in the non-relational database storage for the at least one entity identifier, granting the delegate account a subset of document management functions available for the set of documents.

Abstract: Systems, methods and computer program products for automatically ingesting and filing documents in a database having a plurality of file locations. An electronic file having one or more documents is received. For each document in the received file, text data is identified and used to generate a plurality of suggested file locations for the received documents. Machine learning systems may be used to enhance the accuracy of suggested file locations.

Abstract: Systems, methods and computer program products for automatically ingesting and filing documents in a database having a plurality of file locations. An electronic file having one or more documents is received. For each document in the received file, text data is identified and used to generate a plurality of suggested file locations for the received documents. Machine learning systems may be used to enhance the accuracy of suggested file locations.

Abstract: Systems, methods and computer program products for automatically ingesting and filing documents in a database having a plurality of file locations. An electronic file having one or more documents is received. For each document in the received file, text data is identified and used to generate a plurality of suggested file locations for the received documents. Machine learning systems may be used to enhance the accuracy of suggested file locations.

Abstract: Methods and systems for sharing electronic documents are described herein. The example method includes storing the electronic documents in a relational database storage; storing entity identifiers in the relational database storage, each entity identifier representing an entity type; recording in a non-relational database storage associations between the electronic documents and at least one entity identifier, each association comprising a relationship between a set of electronic documents and the at least one entity identifier; associating a delegate account with the at least one entity identifier; and based on an association recorded in the non-relational database storage for the at least one entity identifier, granting the delegate account a subset of document management functions available for the set of documents.

Abstract: Methods, systems and computer program products for organizing and displaying in real-time data related to a plurality of documents. A plurality of documents and a plurality of entity identifiers are stored in a relational database storage. Each entity identifier has an entity type selected from a plurality of entity types. A plurality of entity associations between the plurality of entity identifiers and the plurality of documents are stored in a non-relational database storage. Each entity association defines a relationship between one or more entity identifiers and a selected document in the plurality of documents. A plurality of file icons are displayed in a display interface. The plurality of file icons includes active icons corresponding to a selection of the plurality of documents where the selection is determined by querying the non-relational database storage using at least one currently-selected entity identifier.