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1. WO2021111267 - DATA AUGMENTED TRAINING OF REINFORCEMENT LEARNING SOFTWARE AGENT

Publication Number WO/2021/111267
Publication Date 10.06.2021
International Application No. PCT/IB2020/061230
International Filing Date 27.11.2020
IPC
G06F 16/00 2019.01
GPHYSICS
06COMPUTING; CALCULATING OR COUNTING
FELECTRIC DIGITAL DATA PROCESSING
16Information retrieval; Database structures therefor; File system structures therefor
G06N 3/02 2006.01
GPHYSICS
06COMPUTING; CALCULATING OR COUNTING
NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
3Computer systems based on biological models
02using neural network models
CPC
G06F 16/24578
GPHYSICS
06COMPUTING; CALCULATING; COUNTING
FELECTRIC DIGITAL DATA PROCESSING
16Information retrieval; Database structures therefor; File system structures therefor
20of structured data, e.g. relational data
24Querying
245Query processing
2457with adaptation to user needs
24578using ranking
G06F 16/83
GPHYSICS
06COMPUTING; CALCULATING; COUNTING
FELECTRIC DIGITAL DATA PROCESSING
16Information retrieval; Database structures therefor; File system structures therefor
80of semi-structured data, e.g. markup language structured data such as SGML, XML or HTML
83Querying
G06K 9/6256
GPHYSICS
06COMPUTING; CALCULATING; COUNTING
KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
9Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
62Methods or arrangements for recognition using electronic means
6217Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
6256Obtaining sets of training patterns; Bootstrap methods, e.g. bagging, boosting
G06N 20/00
GPHYSICS
06COMPUTING; CALCULATING; COUNTING
NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
20Machine learning
G06N 5/02
GPHYSICS
06COMPUTING; CALCULATING; COUNTING
NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
5Computer systems using knowledge-based models
02Knowledge representation
Applicants
  • INTERNATIONAL BUSINESS MACHINES CORPORATION [US]/[US]
  • IBM UNITED KINGDOM LIMITED [GB]/[GB] (MG)
  • IBM (CHINA) INVESTMENT COMPANY LIMITED [CN]/[CN] (MG)
Inventors
  • CHAKRABORTI, Tathagata
  • TALAMADUPULA, Kartik
  • FADNIS, Kshitij
  • SRIVASTAVA, Biplav
  • CAMPBELL, Murray, Scott
Agents
  • SHAW, Anita
Priority Data
16/704,39505.12.2019US
Publication Language English (EN)
Filing Language English (EN)
Designated States
Title
(EN) DATA AUGMENTED TRAINING OF REINFORCEMENT LEARNING SOFTWARE AGENT
(FR) FORMATION AUGMENTÉE DE DONNÉES D’UN AGENT LOGICIEL D’APPRENTISSAGE DE RENFORCEMENT
Abstract
(EN)
Techniques are provided for reinforcement learning software agents enhanced by external data. A reinforcement learning model supporting the software agent may be trained based on information obtained from one or more knowledge stores, such as online forums. The trained reinforcement learning model may be tested in an environment with limited connectivity to an external environment to meet performance criteria. The reinforcement learning software agent may be deployed with the tested and trained reinforcement learning model within an environment to autonomously perform actions to process requests.
(FR)
La présente invention concerne des techniques destinées à des agents logiciels d’apprentissage de renforcement améliorés par des données externes. Un modèle d’apprentissage par renforcement prenant en charge l’agent logiciel peut être formé sur la base d’informations obtenues d’une ou de plusieurs mémoires de connaissances, telles que des forums en ligne. Le modèle d’apprentissage par renforcement formé peut être testé dans un environnement ayant une connectivité limitée à un environnement externe pour satisfaire des critères de performance. L’agent logiciel d’apprentissage de renforcement peut être déployé avec le modèle d’apprentissage de renforcement formé et testé dans un environnement pour réaliser de manière autonome des actions pour traiter des demandes.
Also published as
Latest bibliographic data on file with the International Bureau