Self-Adaptive Organizations for Distributed Search: The Case of Reinforcement Learning

2016 ◽  
pp. 23-32
Author(s):  
Friederike Wall
Keyword(s):  
Reinforcement Learning ◽  
Distributed Search ◽  
Self Adaptive

A Two-Layer Approach to Developing Self-Adaptive Multi-Agent Systems in Open Environment

2014 ◽  
Vol 6 (1) ◽  
pp. 65-85 ◽  
Author(s):  
Xinjun Mao ◽  
Menggao Dong ◽  
Haibin Zhu
Keyword(s):  
Reinforcement Learning ◽  
Adaptive Systems ◽  
Multi Agent Systems ◽  
Uncertain Environments ◽  
Implementation Framework ◽  
Fine Grain ◽  
Adaptation Mechanisms ◽  
Multi Agent ◽  
Self Adaptation ◽  
Self Adaptive

Development of self-adaptive systems situated in open and uncertain environments is a great challenge in the community of software engineering due to the unpredictability of environment changes and the variety of self-adaptation manners. Explicit specification of expected changes and various self-adaptations at design-time, an approach often adopted by developers, seems ineffective. This paper presents an agent-based approach that combines two-layer self-adaptation mechanisms and reinforcement learning together to support the development and running of self-adaptive systems. The approach takes self-adaptive systems as multi-agent organizations and enables the agent itself to make decisions on self-adaptation by learning at run-time and at different levels. The proposed self-adaptation mechanisms that are based on organization metaphors enable self-adaptation at two layers: fine-grain behavior level and coarse-grain organization level. Corresponding reinforcement learning algorithms on self-adaptation are designed and integrated with the two-layer self-adaptation mechanisms. This paper further details developmental technologies, based on the above approach, in establishing self-adaptive systems, including extended software architecture for self-adaptation, an implementation framework, and a development process. A case study and experiment evaluations are conducted to illustrate the effectiveness of the proposed approach.

scholarly journals A Meta Reinforcement Learning-based Approach for Self-Adaptive System

2021 ◽  
Author(s):  
Mingyue Zhang ◽  
Jialong Li ◽  
Haiyan Zhao ◽  
Kenji Tei ◽  
Shinichi Honiden ◽  
...  
Keyword(s):  
Reinforcement Learning ◽  
Adaptive System ◽  
Self Adaptive
Sign in / Sign up

Export Citation Format

Share Document