MULTIPLE-AGENE HYBRID CONTROL ARCHITECTURE FOR INTELLIGENT REAL-TIME CONTROL OF DISTRIBUTED NON-LINEAR PROCESSES

Patent №

US 5,963,447

Granted

1999-10-05

Filed 1997

Owner

HYBRITHMS CORP.

+2 more

Lab

AI components

2

ml · hardware

Assignment

Recorded

Dataset

AIPD

2023_r1 edition

Application

08916418

A Multiple-Agent Hybrid Control Architecture (MAHCA) uses agents to analyze design, and implement intelligent control of distributed processes. A network of agents can be configured to control more complex distributed processes. The network of agents interact to create an emergent global behavior. Global behavior is emergent from individual agent behaviors and is achieved without central control through the imposition of global constraints on the network of individual agent behaviors. Agent synchronization can be achieved by satisfaction of an interagent invariance principle. At each update time, the active plan of each of the agents in the network encodes equivalent behavior modulo a congruence relation determined by the knowledge clauses in each agents's knowledge base. The Control Loop and the Reactive Learning Loop of each agent can be implemented separately. This separation results in an implementation runs faster and with less memory requirements than an unseparated arrangement. A Direct Memory Map (DMM) is to implement the agent architecture. The DMM is a procedure for transforming knowledge and acts as a compiler of agent knowledge by providing a data structure called memory patches, which are used to organize the knowledge contained in each agent's Knowledge Base. Content addressable memory is used as the basic mechanism of the memory patch structure. Content addressable memory uses a specialized register called the comparand to store a pattern that is compared with contents of the memory cells. The DMM has two comparands, the Present State Comparand and the Goal Comparand. The MAHCA can be used for compression/decompression for processing and storage of audio or video data.

Machine learningAI hardwareG05B 19/41865G06N 5/043G05B 2219/33055G05B 2219/33065G05B 2219/33073Y02P 90/02

AI classification

AI hardware1.00
Machine learning0.99
Speech0.29
Knowledge representation0.01
Vision0.00
Evolutionary computation0.00
Natural language0.00
Planning0.00

Ownership

HYBRITHMS CORP.

assignment · 87710937

HYNOMICS CORPORATION

merger · 99250201

CLEARSIGHT SYSTEMS INC.

namechg · 147970455

Assignors

KOHN, WOLF, NERODE, ANIL

On an employer assignment, the assignors are typically the inventors.

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