Telefonaktiebolaget Lm Ericsson (publ)

Klaus Raizer

Konstantinos Vandikas

Amadeu Do Nascimento Junior

Alberto Hata

Jean Paulo Martins

Aneta Vulgarakis Feljan

Ricardo Da Silva Souza

Rafia Inam

Yifei Jin

Ramamurthy Badrinath

Chunyan Fu

Christian Schaefer

André Luis Ogando Paraense

Ricardo Ribeiro Gudwin

Andrii Berezovskyi

In one aspect, a method of determining a risk of conflict between a movable device and potential obstacles is provided. The method includes dividing a space into a plurality of positions. At each of a plurality of successive times, the method further includes: determining a conflict function for the movable device in a first position at a respective time, the first position having one or more neighbouring positions, wherein the conflict function is determined based on whether or not an obstacle is present in any of the first position and the one or more neighbouring positions; and determining a respective risk value for at least one of the first position and the one or more neighbouring positions using the conflict function and a risk value associated with a second position, wherein the movable device is planned to move from the first position to the second position at a subsequent time.

Managing conflicting interactions between a movable device and potential obstacles

A Cognitive Manager (CM) controls a RAN. The CM obtains from the RAN a set of local needs identifying a radio communication performance criterion that is to be satisfied. A set of neighbor needs are obtained from a neighbor CM. An event message is received from the RAN containing a radio metric that does not presently satisfy at least one of the set of local needs. A set of present neighbor improvement action drives being performed or will be performed to satisfy the set of neighbor needs, are obtained from the neighbor CM. A combination of the set of local needs, the set of the neighbor needs, the set of present neighbor improvement action drives, and the radio metric, is used to determine a local improvement action drive that is to be performed by the RAN. An adjustment report identifying the local improvement action drive is provided to the RAN.

Dynamic collaboration among cognitive agents managing radio access networks

Methods and apparatus for implementing reinforcement learning are provided. A method in a client node that instructs actions in an environment in accordance with a policy includes identifying one or more critical states of the environment for which a current policy provides unreliable actions. The method further includes initiating transmission to a server of a retraining request, the retraining request having information relating to the one or more critical states. The method further includes receiving a new policy from the server, wherein the new policy is generated by the server using reinforcement learning based on the information relating to the one or more critical states, and instructing actions in the environment in accordance with the new policy.

Machine-learning models and apparatus

According to embodiments herein e.g. a method performed by an orchestration agent unit for handling a service in a communications network is provided. The orchestration agent unit evaluate a number of intent types of the service based on a performance of one or more performance metrics related to intent of respective intent type when performed in the communications network including a plurality of orchestration agent units. The orchestration agent unit selects an intent type of the service based on the evaluation; and sends to at least one of the plurality of orchestration agent units, an indication indicating the selected intent type of the service.

Orchestration agent unit and method therein in a communications network

A method and a communication device for determining a score relating to a first agent module are described. The communication device receives information relating to at least one request, performed by another agent module separate from the first agent module, for consumption of a capability of the first agent module. The information relating to the at least one request includes information about the capability of the first agent module, information about an intention of the first agent module, and information about a policy for the capability. The communication device calculates the score in relation to the first agent module based on the information relating to the at least one request, wherein the score further is specified with respect to the capability.

Method and communication device for determining a score relating to a first agent module

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Indaiatuba, Brazil

Klaus Raizer