# US 2021/0279619 A1 · Federated artificial intelligence with cumulative learning in a computer network

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- Number: US 2021/0279619 A1
- Document ID: US20210279619A1
- Status: Published application
- Kind: A1
- Application number: 16/811,806
- Filed: 2020-03-06
- Published: 2021-09-09
- Earliest claimed: 2020-03-06
- Assignees: Cisco Technology, Inc.
- Applicants: Cisco Technology, Inc.
- Inventors: Hugo Latapie; Enzo Fenoglio; Carlos M. Pignataro; Nagendra Kumar Nainar; David Delano Ward
- Web page: https://patentgrep.com/patent/US20210279619A1

## CPC

- G06F 16/27: Replication, distribution or synchronisation of data between databases or within a distributed database system; Distributed database system architectures therefor
- G06N 3/042: Knowledge-based neural networks; Logical representations of neural networks
- G06N 5/02: Knowledge representation; Symbolic representation
- G06N 5/022: Knowledge engineering; Knowledge acquisition
- G06N 5/043: Distributed expert systems; Blackboards
- G06N 5/048: Fuzzy inferencing
- G06N 20/00: Machine learning
- G06N 5/046: Forward inferencing; Production systems
- G06N 20/10: using kernel methods, e.g. support vector machines [SVM]
- G06N 20/20: Ensemble learning
- G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N)
- G06N: COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS

## Abstract

In one embodiment, a first deep fusion reasoning engine (DFRE) agent in a network receives first sensor data from a first set of one or more sensors in the network. The first DFRE agent translates the first sensor data into symbolic data. The first DFRE agent applies, using a symbolic knowledge base maintained by the first DFRE agent, symbolic reasoning to the symbolic data to make an inference regarding the first sensor data. The first DFRE agent updates, based on the inference regarding the first sensor data, the knowledge base. The first DFRE agent propagates the inference to one or more other DFRE agents in the network.

## Claims

### Claim 1

A method comprising:
receiving, at a first deep fusion reasoning engine (DFRE) agent in a network, first sensor data from a first set of one or more sensors in the network;
translating, by the first DFRE agent, the first sensor data into symbolic data;
applying, by the first DFRE agent and using a symbolic knowledge base maintained by the first DFRE agent, symbolic reasoning to the symbolic data to make an inference regarding the first sensor data;
updating, by the first DFRE agent and based on the inference regarding the first sensor data, the knowledge base; and
propagating, by the first DFRE agent, the inference to one or more other DFRE agents in the network.

### Claim 2 (depends on 1)

The method as in claim 1, further comprising:
initiating the symbolic knowledge base with a seed ontology.

### Claim 3 (depends on 1)

The method as in claim 1, wherein propagating the inference to the one or more other DFRE agents in the network comprises:
publishing, by the first DFRE agent, the inference to an in-memory database server in the network, wherein the one or more other DFRE agents subscribe to the server.

### Claim 4 (depends on 1)

The method as in claim 1, wherein the one or more other DFRE agents receive second sensor data from a second set of one or more sensors, and wherein the one or more other DFRE agents analyze the second sensor data using the inference propagated by the first DFRE agent.

### Claim 5 (depends on 1)

The method as in claim 1, further comprising:
computing, by the first DFRE agent, a length of a chain of reasoning associated with the inference; and
determining, by the first DFRE agent, that the inference should be propagated to the one or more other DFRE agents, based on the computed length of the chain of reasoning associated with the inference.

### Claim 6 (depends on 1)

The method as in claim 1, further comprising:
identifying, by the first DFRE agent, a class of event associated with the inference; and
determining, by the first DFRE agent, that the inference should be propagated to the one or more other DFRE agents, based on the class of event associated with the inference.

### Claim 7 (depends on 1)

The method as in claim 1, wherein the one or more sensors comprise a camera, and wherein the first sensor data comprises a video stream.

### Claim 8 (depends on 1)

The method as in claim 1, further comprising:
receiving, at the first DFRE agent, an inference made by one of the one or more other DFRE agents in the network; and
updating, by the first DFRE agent and based on the received inference, the symbolic knowledge base maintained by the first DFRE agent.

### Claim 9 (depends on 1)

The method as in claim 1, further comprising:
receiving, at the first DFRE agent, an indication of a focus of attention for the first sensor data, wherein the first DFRE agent applies symbolic reasoning to the symbolic data based in part on the focus of attention.

### Claim 10

An apparatus, comprising:
one or more network interfaces to communicate with a network;
a processor coupled to the one or more network interfaces and configured to execute one or more processes; and
a memory configured to store a process executable by the processor, the process when executed configured to:
receive first sensor data from a first set of one or more sensors in the network;
translate, by a first DFRE agent executed by the apparatus, the first sensor data into symbolic data;
apply, by the first DFRE agent and using a symbolic knowledge base maintained by the first DFRE agent, symbolic reasoning to the symbolic data to make an inference regarding the first sensor data;
update, by the first DFRE agent and based on the inference regarding the first sensor data, the knowledge base; and
propagate the inference to one or more other DFRE agents in the network.

### Claim 11 (depends on 10)

The apparatus as in claim 10, wherein the process when executed is further configured to:
initiate the symbolic knowledge base with a seed ontology.

### Claim 12 (depends on 10)

The apparatus as in claim 10, wherein the apparatus propagates the inference to the one or more other DFRE agents in the network by:
publishing the inference to an in-memory database server in the network, wherein the one or more other DFRE agents subscribe to the server.

### Claim 13 (depends on 10)

The apparatus as in claim 10, wherein the one or more other DFRE agents receive second sensor data from a second set of one or more sensors, and wherein the one or more other DFRE agents analyze the second sensor data using the inference propagated by the first DFRE agent.

### Claim 14 (depends on 10)

The apparatus as in claim 10, wherein the process when executed is further configured to:
compute a length of a chain of reasoning associated with the inference; and
determine that the inference should be propagated to the one or more other DFRE agents, based on the computed length of the chain of reasoning associated with the inference.

### Claim 15 (depends on 10)

The apparatus as in claim 10, wherein the process when executed is further configured to:
identify a class of event associated with the inference; and
determine that the inference should be propagated to the one or more other DFRE agents, based on the class of event associated with the inference.

### Claim 16 (depends on 10)

The apparatus as in claim 10, wherein the one or more sensors comprise a camera, and wherein the first sensor data comprises a video stream.

### Claim 17 (depends on 10)

The apparatus as in claim 10, wherein the process when executed is further configured to:
receive an inference made by one of the one or more other DFRE agents in the network; and
update, based on the received inference, the symbolic knowledge base maintained by the first DFRE agent.

### Claim 18 (depends on 10)

The apparatus as in claim 10, wherein the process when executed is further configured to:
receive an indication of a focus of attention for the first sensor data, wherein the first DFRE agent applies symbolic reasoning to the symbolic data based in part on the focus of attention.

### Claim 19

A tangible, non-transitory, computer-readable medium storing program instructions that cause a first deep fusion reasoning engine (DFRE) agent in a network to execute a process comprising:
receiving, at the first DFRE agent, first sensor data from a first set of one or more sensors in the network;
translating, by the first DFRE agent, the first sensor data into symbolic data;
applying, by the first DFRE agent and using a symbolic knowledge base maintained by the first DFRE agent, symbolic reasoning to the symbolic data to make an inference regarding the first sensor data;
updating, by the first DFRE agent and based on the inference regarding the first sensor data, the knowledge base; and
propagating, by the first DFRE agent, the inference to one or more other DFRE agents in the network.

### Claim 20 (depends on 19)

The computer-readable medium as in claim 19, wherein propagating the inference to the one or more other DFRE agents in the network comprises:
publishing, by the first DFRE agent, the inference to an in-memory database server in the network, wherein the one or more other DFRE agents subscribe to the server.