Realizing the NOSHAPE MAS Organizational Model

2015 ◽  
Vol 7 (2) ◽  
pp. 75-104 ◽  
Author(s):  
Hosny Ahmed Abbas
Keyword(s):  
Large Scale ◽  
Real Life ◽  
Research Area ◽  
Multi Agent Systems ◽  
Organizational Model ◽  
Design Decisions ◽  
Agent Systems ◽  
Multi Agent ◽  
Active Research ◽  
Great Focus

Dynamic reorganization of multi-agent systems (MAS) is currently an interesting and active research area. New emerging concepts such as self-organization and emergence are also getting great focus by MAS research community because of their captivating benefits for engineering complex large-scale MAS applications. Dynamic reorganization is considered as an effective way for building adaptive MAS. This paper provides an operational view of the conceptually proposed NOSHAPE dynamic organizational model for dynamically reorganized multi-agent systems (Abbas, 2014). The operational view concerns possible design decisions, implementation issues, and suggested usage of the NOSHAPE model for practically engineering real life applications. This paper also identifies the possible solutions to be applied throughout the system design to resolve these concerns.

scholarly journals Representation and Reasoning about Strategic Abilities with ω-Regular Properties

Mathematics ◽  
2021 ◽  
Vol 9 (23) ◽  
pp. 3052
Author(s):  
Liping Xiong ◽  
Sumei Guo
Keyword(s):  
Temporal Logic ◽  
Linear Time ◽  
Dynamic Logic ◽  
Research Area ◽  
Regular Expressions ◽  
Multi Agent Systems ◽  
Practical Applications ◽  
Multi Agent ◽  
Strategy Logic ◽  
Active Research

Specification and verification of coalitional strategic abilities have been an active research area in multi-agent systems, artificial intelligence, and game theory. Recently, many strategic logics, e.g., Strategy Logic (SL) and alternating-time temporal logic (ATL*), have been proposed based on classical temporal logics, e.g., linear-time temporal logic (LTL) and computational tree logic (CTL*), respectively. However, these logics cannot express general ω-regular properties, the need for which are considered compelling from practical applications, especially in industry. To remedy this problem, in this paper, based on linear dynamic logic (LDL), proposed by Moshe Y. Vardi, we propose LDL-based Strategy Logic (LDL-SL). Interpreted on concurrent game structures, LDL-SL extends SL, which contains existential/universal quantification operators about regular expressions. Here we adopt a branching-time version. This logic can express general ω-regular properties and describe more programmed constraints about individual/group strategies. Then we study three types of fragments (i.e., one-goal, ATL-like, star-free) of LDL-SL. Furthermore, we show that prevalent strategic logics based on LTL/CTL*, such as SL/ATL*, are exactly equivalent with those corresponding star-free strategic logics, where only star-free regular expressions are considered. Moreover, results show that reasoning complexity about the model-checking problems for these new logics, including one-goal and ATL-like fragments, is not harder than those of corresponding SL or ATL*.

scholarly journals Trust in multi-agent systems

2004 ◽  
Vol 19 (1) ◽  
pp. 1-25 ◽  
Author(s):  
SARVAPALI D. RAMCHURN ◽  
DONG HUYNH ◽  
NICHOLAS R. JENNINGS
Keyword(s):  
Large Scale ◽  
State Of The Art ◽  
Comprehensive Treatment ◽  
Multi Agent Systems ◽  
Agent Based ◽  
Agent Systems ◽  
The Core ◽  
Open Distributed Systems ◽  
Multi Agent

Trust is a fundamental concern in large-scale open distributed systems. It lies at the core of all interactions between the entities that have to operate in such uncertain and constantly changing environments. Given this complexity, these components, and the ensuing system, are increasingly being conceptualised, designed, and built using agent-based techniques and, to this end, this paper examines the specific role of trust in multi-agent systems. In particular, we survey the state of the art and provide an account of the main directions along which research efforts are being focused. In so doing, we critically evaluate the relative strengths and weaknesses of the main models that have been proposed and show how, fundamentally, they all seek to minimise the uncertainty in interactions. Finally, we outline the areas that require further research in order to develop a comprehensive treatment of trust in complex computational settings.

Adaptive Agent Selection in Large-Scale Multi-Agent Systems

2006 ◽  
pp. 818-822
Author(s):  
Toshiharu Sugawara ◽  
Kensuke Fukuda ◽  
Toshio Hirotsu ◽  
Shin-ya Sato ◽  
Satoshi Kurihara
Keyword(s):  
Large Scale ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Adaptive Agent ◽  
Agent Selection ◽  
Multi Agent

How Can We Trust Agents in Multi-Agent Environments? Techniques and Challenges

2009 ◽  
pp. 2843-2864 ◽  
Author(s):  
Kostas Kolomvatsos ◽  
Stathes Hadjiefthymiades
Keyword(s):  
Computer Science ◽  
Research Area ◽  
Software Components ◽  
Important Research ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Potential Partner ◽  
Multi Agent ◽  
Important Research Area

The field of Multi-agent systems (MAS) has been an active area for many years due to the importance that agents have to many disciplines of research in computer science. MAS are open and dynamic systems where a number of autonomous software components, called agents, communicate and cooperate in order to achieve their goals. In such systems, trust plays an important role. There must be a way for an agent to make sure that it can trust another entity, which is a potential partner. Without trust, agents cannot cooperate effectively and without cooperation they cannot fulfill their goals. Many times, trust is based on reputation. It is an indication that we may trust someone. This important research area is investigated in this book chapter. We discuss main issues concerning reputation and trust in MAS. We present research efforts and give formalizations useful for understanding the two concepts.

Incremental Distributed Learning with JavaScript Agents for Earthquake and Disaster Monitoring

2017 ◽  
Vol 8 (4) ◽  
pp. 34-53 ◽  
Author(s):  
Stefan Bosse
Keyword(s):  
Mobile Agents ◽  
Large Scale ◽  
Learning Algorithm ◽  
Seismic Station ◽  
Geodetic Network ◽  
Distributed Learning ◽  
The Internet ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Multi Agent

Ubiquitous computing and The Internet-of-Things (IoT) grow rapidly in today's life and evolving to Self-organizing systems (SoS). A unified and scalable information processing and communication methodology is required. In this work, mobile agents are used to merge the IoT with Mobile and Cloud environments seamless. A portable and scalable Agent Processing Platform (APP) provides an enabling technology that is central for the deployment of Multi-Agent Systems (MAS) in strong heterogeneous networks including the Internet. A large-scale use-case deploying Multi-agent systems in a distributed heterogeneous seismic sensor and geodetic network is used to demonstrate the suitability of the MAS and platform approach. The MAS is used for earthquake monitoring based on a new incremental distributed learning algorithm applied to seismic station data, which can be extended by ubiquitous sensing devices like smart phones. Different (mobile) agents perform sensor sensing, aggregation, local learning and prediction, global voting and decision making, and the application.

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