View source for 17528486. GENERATING LOGICALLY-REPRESENTED POLICY FOR CONTROL SYSTEMS OPERATING BASED ON CONSTRAINED MARKOV DECISION PROCESS (CMDP) MODELS simplified abstract (International Business Machines Corporation)

=GENERATING LOGICALLY-REPRESENTED POLICY FOR CONTROL SYSTEMS OPERATING BASED ON CONSTRAINED MARKOV DECISION PROCESS (CMDP) MODELS=


==Organization Name==

[[:Category:International Business Machines Corporation|International Business Machines Corporation]]


[[Category:International Business Machines Corporation]]

==Inventor(s)==

[[:Category:Alexander Zadorojniy of Haifa (IL)|Alexander Zadorojniy of Haifa (IL)]][[Category:Alexander Zadorojniy of Haifa (IL)]]

[[:Category:Yishai Abraham Feldman of Tel Aviv (IL)|Yishai Abraham Feldman of Tel Aviv (IL)]][[Category:Yishai Abraham Feldman of Tel Aviv (IL)]]

[[:Category:Lan Ngoc Hoang of Lymm (GB)|Lan Ngoc Hoang of Lymm (GB)]][[Category:Lan Ngoc Hoang of Lymm (GB)]]

==GENERATING LOGICALLY-REPRESENTED POLICY FOR CONTROL SYSTEMS OPERATING BASED ON CONSTRAINED MARKOV DECISION PROCESS (CMDP) MODELS - A simplified explanation of the abstract==


This abstract first appeared for US patent application 17528486 titled 'GENERATING LOGICALLY-REPRESENTED POLICY FOR CONTROL SYSTEMS OPERATING BASED ON CONSTRAINED MARKOV DECISION PROCESS (CMDP) MODELS

==Simplified Explanation==

The patent application describes a control system that generates a policy for operating a controlled application system. The control system receives data related to control action variables, system state variables, cost/reward, and constraints. It then automatically trains a CMDP (Constrained Markov Decision Process) model using dual linear programming. The CMDP model includes a policy based on occupation measures. The control system further generates a logically-represented policy based on the CMDP model.

* Control system generates a policy for operating a controlled application system
* Receives data related to control action variables, system state variables, cost/reward, and constraints
* Automatically trains a CMDP model using dual linear programming
* CMDP model includes a policy based on occupation measures
* Control system generates a logically-represented policy based on the CMDP model

== Potential Applications ==
* Industrial automation systems
* Traffic control systems
* Energy management systems
* Robotics and autonomous systems

== Problems Solved ==
* Efficiently generating policies for control systems
* Handling constraints in the operation of controlled application systems
* Optimizing cost/reward trade-offs in decision-making

== Benefits ==
* Improved control system performance
* Enhanced decision-making capabilities
* Increased efficiency and productivity in various applications
* Better resource allocation and utilization


==Original Abstract Submitted==

A control system, computer program product, and method for generating a logically-represented policy for a control system operating based on a CMDP model are provided. The control system directs the operation of a controlled application system that is subject to a constraint. The method includes receiving, at the control system, data corresponding to control action variables and system state variables relating to the controlled application system, data corresponding to a cost/reward, and data corresponding to the constraint, and automatically training a CMDP model for the operation of the controlled application system based on the received data, where the CMDP model is formulated using dual linear programming, and where the CMDP model includes a policy corresponding to occupation measures that are decision variables of the dual linear programming formulation. The method also includes automatically generating a logically-represented policy for the control system based on the policy of the CMDP model.



[[Category:G05B17/02]]
[[Category:G06N7/00]]