2016 IEEE 10th International Conference on Self-Adaptive and Self-Organizing Systems (SASO)最新文献

Learning in Open Adaptive Networks 开放自适应网络中的学习

2016 IEEE 10th International Conference on Self-Adaptive and Self-Organizing Systems (SASO) Pub Date : 2016-12-08 DOI: 10.1109/SASO.2016.11

Guoli Yang, Vincent Danos

{"title":"Learning in Open Adaptive Networks","authors":"Guoli Yang, Vincent Danos","doi":"10.1109/SASO.2016.11","DOIUrl":"https://doi.org/10.1109/SASO.2016.11","url":null,"abstract":"We propose a generic distributed learn-and-adapt model for high performance and high resilience configuration of open cooperative agent networks. Agents are involved into three interconnected types of activities. Firstly, agents bid for participation to the processing of a steady random flow of structured tasks. Secondly, agents learn the (exogenous) features of the random task source, by aggregating local information (such as success rates, average load, etc). And, thirdly, agents adapt the composition of their neighbourhoods following the (endogenous) targets set by their learning process. Neighbourhood readjustment proceeds by judicious rewiring steps which stay entirely local. Thus an agent continuously works, adjusts its neighbourhood, and based on his local metrics, learns how to inflect its own adaptation targets. Because of this tight coupling of all three activities, the network as a whole can reconfigure in a fully decentralized way to cope with changes in: the network composition (node failures, new incoming nodes, etc), and the parameters of the task source (changes in the size, structure, and frequency), while attaining robustly a near-optimal performance level (compared to the centralised solution).","PeriodicalId":383753,"journal":{"name":"2016 IEEE 10th International Conference on Self-Adaptive and Self-Organizing Systems (SASO)","volume":"90 12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116302455","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

An Evolutionary Robotics Approach to the Control of Plant Growth and Motion: Modeling Plants and Crossing the Reality Gap 植物生长和运动控制的进化机器人方法:植物建模和跨越现实差距

2016 IEEE 10th International Conference on Self-Adaptive and Self-Organizing Systems (SASO) Pub Date : 2016-12-08 DOI: 10.1109/SASO.2016.8

Mostafa Wahby, D. Hofstadler, Mary Katherine Heinrich, Payam Zahadat, Heiko Hamann

引用次数: 19

Losing Control: The Case for Emergent Software Systems Using Autonomous Assembly, Perception, and Learning 失去控制:使用自主装配、感知和学习的紧急软件系统的案例

2016 IEEE 10th International Conference on Self-Adaptive and Self-Organizing Systems (SASO) Pub Date : 2016-12-08 DOI: 10.1109/SASO.2016.10

Barry Porter, Roberto Rodrigues Filho

{"title":"Losing Control: The Case for Emergent Software Systems Using Autonomous Assembly, Perception, and Learning","authors":"Barry Porter, Roberto Rodrigues Filho","doi":"10.1109/SASO.2016.10","DOIUrl":"https://doi.org/10.1109/SASO.2016.10","url":null,"abstract":"Architectural self-organisation, in which different configurations of software modules are dynamically assembled based on the current context, has been shown to be an effective way for software to self-optimise over time. Current approaches to this rely heavily on human-led definitions: models, policies and processes to control how self-organisation works. We present the case for a paradigm shift to fully emergent computer software which places the burden of understanding entirely into the hands of software itself. These systems are autonomously assembled at runtime from discovered constituent parts and their internal health and external deployment environment continually monitored. An online, unsupervised learning system then uses runtime adaptation to explore alternative system assemblies and locate optimal solutions. Based on our experience to date, we define the problem space of emergent software, and we present a working case study of an emergent web server. Our results demonstrate two aspects of the problem space for this case study: that different assemblies of behaviour are optimal in different deployment environment conditions, and that these assemblies can be autonomously learned from generalised perception data while the system is online.","PeriodicalId":383753,"journal":{"name":"2016 IEEE 10th International Conference on Self-Adaptive and Self-Organizing Systems (SASO)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121245682","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 21

Interaction-Awareness for Self-Adaptive Volunteer Computing 自适应志愿计算的交互意识

2016 IEEE 10th International Conference on Self-Adaptive and Self-Organizing Systems (SASO) Pub Date : 2016-12-08 DOI: 10.1109/SASO.2016.24

Abdessalam Elhabbash, R. Bahsoon, P. Tiňo

引用次数: 2

Flexible Load Shedding Using Gossip Communication in a Multi-agents System 多智能体系统中基于八卦通信的灵活减载

2016 IEEE 10th International Conference on Self-Adaptive and Self-Organizing Systems (SASO) Pub Date : 2016-09-12 DOI: 10.1109/SASO.2016.9

Victor Lequay, Mathieu Lefort, Saber Mansour, S. Hassas

引用次数: 3

Inter-institutional Social Capital for Self-Organising 'Nested Enterprises' 自组织“嵌套企业”的机构间社会资本

2016 IEEE 10th International Conference on Self-Adaptive and Self-Organizing Systems (SASO) Pub Date : 2016-09-01 DOI: 10.1109/SASO.2016.15

Patricio E. Petruzzi, J. Pitt, D. Busquets

{"title":"Inter-institutional Social Capital for Self-Organising 'Nested Enterprises'","authors":"Patricio E. Petruzzi, J. Pitt, D. Busquets","doi":"10.1109/SASO.2016.15","DOIUrl":"https://doi.org/10.1109/SASO.2016.15","url":null,"abstract":"A self-governing institution designed according to Ostrom's principles provides a way for its members to self-organise the management and sustainability of common-pool resources. Such institutions have been studied as a form of social capital, used as an input to a decision-making framework for coordination in various collective action situations. It has been shown that formally representing and reasoning with (electronic) social capital can reduce the complexity of decision-making, enhance participation and improve outcomes of collective action. However, it was assumed that these institutions were essentially independent, and so the members were limited in their ability to fully exploit their social capital across different collective actions situations because they did no learning. Therefore, in this paper we examine the role and nature of social capital with learning agents in the context of Ostrom's institutional design principle regarding structural self-organisation, specifically in the form of multiple layers of nested enterprises. Both inter-agent and inter-institutional interactions are then situated in a Public Goods Game, typically used to study the effects of free-riding which diminishes the positive benefits of cooperation in otherwise unregulated situations. Our experimental results demonstrate that the Social Capital created both within and between the institutions beneficially affects the development of a bottom-up structure of nested enterprises.","PeriodicalId":383753,"journal":{"name":"2016 IEEE 10th International Conference on Self-Adaptive and Self-Organizing Systems (SASO)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126026635","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 6

Towards Linking Adaptation Rules to the Utility Function for Dynamic Architectures 动态体系结构自适应规则与效用函数的关联研究

2016 IEEE 10th International Conference on Self-Adaptive and Self-Organizing Systems (SASO) Pub Date : 2016-09-01 DOI: 10.1109/SASO.2016.21

Sona Ghahremani, H. Giese, T. Vogel

引用次数: 5

Hybrid Planning for Decision Making in Self-Adaptive Systems 自适应系统决策的混合规划

2016 IEEE 10th International Conference on Self-Adaptive and Self-Organizing Systems (SASO) Pub Date : 2016-09-01 DOI: 10.1109/SASO.2016.19

Ashutosh Pandey, Gabriel A. Moreno, J. Cámara, D. Garlan

{"title":"Hybrid Planning for Decision Making in Self-Adaptive Systems","authors":"Ashutosh Pandey, Gabriel A. Moreno, J. Cámara, D. Garlan","doi":"10.1109/SASO.2016.19","DOIUrl":"https://doi.org/10.1109/SASO.2016.19","url":null,"abstract":"Run-time generation of adaptation plans is a powerful mechanism that helps a self-adaptive system to meet its goals in a dynamically changing environment. In the past, researchers have demonstrated successful use of various automated planning techniques to generate adaptation plans at run time. However, for a planning technique, there is often a trade-off between timeliness and optimality of the solution. For some self-adaptive systems, ideally, one would like to have a planning approach that is both quick and finds an optimal adaptation plan. To find the right balance between these conflicting requirements, this paper introduces a hybrid planning approach that combines more than one planner to obtain the benefits of each. In this paper, to instantiate a hybrid planner we combine deterministic planning with Markov Decision Process (MDP) planning to obtain the best of both worlds: deterministic planning provides plans quickly when timeliness is critical, while allowing MDP planning to generate optimal plans when the system has sufficient time to do so. We validate the hybrid planning approach using a realistic workload pattern in a simulated cloud-based self-adaptive system.","PeriodicalId":383753,"journal":{"name":"2016 IEEE 10th International Conference on Self-Adaptive and Self-Organizing Systems (SASO)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121123660","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 39

Ensemble Time Series Forecasting with XCSF 集成时间序列预测与XCSF

2016 IEEE 10th International Conference on Self-Adaptive and Self-Organizing Systems (SASO) Pub Date : 2016-09-01 DOI: 10.1109/SASO.2016.25

M. Sommer, Anthony Stein, J. Hähner

引用次数: 3

Self-Organized Graph-Based Resource Allocation 基于自组织图的资源分配

2016 IEEE 10th International Conference on Self-Adaptive and Self-Organizing Systems (SASO) Pub Date : 2016-09-01 DOI: 10.1109/SASO.2016.18

Gerrit Anders, Patrick Lehner

{"title":"Self-Organized Graph-Based Resource Allocation","authors":"Gerrit Anders, Patrick Lehner","doi":"10.1109/SASO.2016.18","DOIUrl":"https://doi.org/10.1109/SASO.2016.18","url":null,"abstract":"In many technical systems, such as smart grids, the central issue is to enable multiple devices to solve a resource allocation problem. Because centralized solutions usually struggle with an increasing number of agents, regio-central or completely decentralized mechanisms, which solve the problem in a cooperative manner, are of utmost interest in large-scale systems. In this paper, we present a coalition-based algorithm that allows a multi-agent system to cooperatively solve a single-resource allocation problem. Our approach uses self-organization to dynamically identify groups of agents whose decisions have to be coordinated, while optimistically refraining from coordinating the actions between these coalitions. The basic idea of our algorithm is inspired by the way pressure compensates in gas or fluid pipeline systems. It therefore operates on the basis of an overlay network, i.e., a graph, that defines a topology of possible resource flows as well as resistances in the form of costs of transferring a resource from one agent to another. Throughout this paper, the problem of compensating for imbalances between energy production and consumption in autonomous power management systems serves to illustrate our algorithm and results.","PeriodicalId":383753,"journal":{"name":"2016 IEEE 10th International Conference on Self-Adaptive and Self-Organizing Systems (SASO)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128508328","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1