Membrane Computing Based Scalable Distributed Learning and Collaborative Decision Making for Cyber Physical Systems
- Resource Type
- Conference
- Authors
- Rai, Ankush; Kannan, R. Jagadeesh
- Source
- 2017 IEEE 26th International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE) WETICE Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE), 2017 IEEE 26th International Conference on. :24-27 Jun, 2017
- Subject
- Computing and Processing
Neurons
Mathematical model
Computational modeling
Collaboration
Decision making
Manufacturing
Robots
Cyber Physical System
Industry 4.0
distributed learning
decision making
- Language
Machine to Machine based communication and coordination in cyber physical systems for manufacturing application is a daunting problem. Here, the difficulty is in developing a multi task learning algorithm for finding collaborative key points within high dimensional decision space. In order to overcome such a problem a gradient based method is required to enable distributed control and collaborative decision making. This paper presents membrane computing based gradient method for online multitask learning and controlling the distributed coordination to achieve stochastic planning to formulate optimize semantic network to derive a local optimal policy. Experimental verification is achieved through implementation of several concurrent functioning of mobile robotic platforms.