MULTIPLE-AGENT HYBRID CONTROL ARCHITECTURE FOR INTELLIGENT REAL-TIME CONTROL OF DISTRIBUTED NONLINEAR PROCESSES

Patent №

US 6,088,689

Granted

2000-07-11

Filed 1995

Owner

HYBRITHMS CORP.

+2 more

Lab

AI components

4

ml · kr · planning · hardware

Assignment

Recorded

Dataset

AIPD

2023_r1 edition

Application

08564008

A Multiple-Agent Hybrid Control Architecture (MAHCA) uses agents to analyze design, and implement intelligent control of distributed processes. A single agent can be configured to control a local process and a network of agents can be configured to control more complex distributed processes. Multiple agents interact through messages and can be either permanent or temporary. The network of agents interact to create an emergent global behavior. The network of agents support construction of closed-loop, autonomous systems which react to comply with two degrees of freedom: (1) a logic degree of freedom (useful for implementing switching between modes of control) and (2) an evolution degree of freedom (useful for implementing particular modes of control). 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 (the logic agent network). MAHCA is especially useful for reactive synchronization of real-time distributed processes subject to decision-making under uncertainty where both logical and evolution constraints on system operation must be continuously maintained and where human operators must be kept appraised of current system operation and whose decisions must be promptly and safely executed. MAHCA also provides support for reuse of existing trusted components and incremental provision of expanded functionality in old or new components through formal construction of provably correct real-time software from declarations of desired logic and evolution behavior of system components. Finally, MAHCA agents can be used in conventional digital procedures to speed up an ensemble of procedures.

Machine learningKnowledge representationPlanningAI hardwareG05B 19/41865G05B 13/0265G05B 19/4148G06N 5/043G05B 2219/33055G05B 2219/33068G05B 2219/33073G05B 2219/33277+1 more

AI classification

Planning1.00
Machine learning0.99
AI hardware0.98
Knowledge representation0.71
Natural language0.35
Vision0.01
Speech0.00
Evolutionary computation0.00

Ownership

HYBRITHMS CORP.

namechg · 84970910

SAGENT CORP. (ALSO KNOWN AS SAGENT CORPORATION)

assignment · 84990837

HYNOMICS CORPORATION

merger · 104590342

Assignors

KOHN, WOLFQ, NERODE, ANIL, JAMES, JOHN

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

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