Authors:
Ashwin Devanga
1
and
Koichiro Yamauchi
2
Affiliations:
1
Indian Institute of Technology Guwahati, Guwahati and India
;
2
Centre of Engineering, Chubu University, Kasugai-shi, Aichi and Japan
Keyword(s):
Actor-Critic Model, Kernel Machine, Learning on a Budget, Super Neural Network, Colbagging, Supervised Learning, Reinforcement Learning, Collaborative Learning Scheme between Human and Learning Machine.
Related
Ontology
Subjects/Areas/Topics:
Ensemble Methods
;
Knowledge Acquisition and Representation
;
Pattern Recognition
;
Theory and Methods
Abstract:
Recent large-scale neural networks show a high performance to complex recognition tasks but to get such ability, it needs a huge number of learning samples and iterations to optimize it’s internal parameters. However, under unknown environments, learning samples do not exist. In this paper, we aim to overcome this problem and help improve the learning capability of the system by sharing data between multiple systems. To accelerate the optimization speed, the novel system forms a collaboration with human and reinforcement learning neural network and for data sharing between systems to develop a super neural network.