Multi-Agent Systems Research and Social Science Theory Building

2007 ◽  
pp. 101-110
Author(s):  
H. Verhagen
Keyword(s):  
Social Science ◽  
Organization Theory ◽  
Social Science Research ◽  
Science Research ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Research Areas ◽  
Systems Research ◽  
Science Theory ◽  
Multi Agent

This chapter describes the possible relationship between multi-agent systems research and social science research, more particularly sociology. It gives examples of the consequences and possibilities of these relationships, and describes some of the important issues and concepts in each of these areas. It finally points out some future directions for a bi-directional relationship between the social sciences and multi-agent systems research which hopefully will help researchers in both research areas, as well as researchers in management and organization theory.

Practical and theoretical innovations in multi-agent systems research

2002 ◽  
Vol 17 (3) ◽  
pp. 295-301
Author(s):  
MARK DINVERNO ◽  
MICHAEL LUCK ◽  
UKMAS 2001 Contributors
Keyword(s):  
Multi Agent Systems ◽  
Agent Systems ◽  
Systems Research ◽  
Multi Agent

scholarly journals Introduction to the special issue on ontologies in agent systems

2002 ◽  
Vol 17 (1) ◽  
pp. 1-5 ◽  
Author(s):  
STEPHEN CRANEFIELD ◽  
STEVEN WILLMOTT ◽  
TIM FININ
Keyword(s):  
Speech Acts ◽  
Coupled System ◽  
Knowledge Bases ◽  
Message Content ◽  
Multi Agent Systems ◽  
Distributed Information ◽  
Agent Systems ◽  
Loosely Coupled ◽  
Systems Research ◽  
Multi Agent

It is now more than ten years since researchers in the US Knowledge Sharing Effort envisaged a future where complex systems could be built by combining knowledge and services from multiple knowledge bases and the first agent communication language, KQML, was proposed (Neches et al., 1991). This model of communication, based on speech acts, a declarative message content representation language and the use of explicit ontologies defining the domains of discourse (Genesereth & Ketchpel, 1994), has become widely recognised as having great benefits for the integration of disparate and distributed information sources to form an open, extensible and loosely coupled system. In particular, this idea has become a key tenet in the multi-agent systems research community.

scholarly journals Cooperative Information Sharing to Improve Distributed Learning in Multi-Agent Systems

2005 ◽  
Vol 24 ◽  
pp. 407-463 ◽  
Author(s):  
P. S. Dutta ◽  
N. R. Jennings ◽  
L. Moreau
Keyword(s):  
Information Sharing ◽  
Formal Analysis ◽  
Empirical Evaluation ◽  
Task Completion ◽  
Multi Agent Systems ◽  
Long Distance ◽  
State Information ◽  
Agent Systems ◽  
Systems Research ◽  
Multi Agent

Effective coordination of agents' actions in partially-observable domains is a major challenge of multi-agent systems research. To address this, many researchers have developed techniques that allow the agents to make decisions based on estimates of the states and actions of other agents that are typically learnt using some form of machine learning algorithm. Nevertheless, many of these approaches fail to provide an actual means by which the necessary information is made available so that the estimates can be learnt. To this end, we argue that cooperative communication of state information between agents is one such mechanism. However, in a dynamically changing environment, the accuracy and timeliness of this communicated information determine the fidelity of the learned estimates and the usefulness of the actions taken based on these. Given this, we propose a novel information-sharing protocol, post-task-completion sharing, for the distribution of state information. We then show, through a formal analysis, the improvement in the quality of estimates produced using our strategy over the widely used protocol of sharing information between nearest neighbours. Moreover, communication heuristics designed around our information-sharing principle are subjected to empirical evaluation along with other benchmark strategies (including Littman's Q-routing and Stone's TPOT-RL) in a simulated call-routing application. These studies, conducted across a range of environmental settings, show that, compared to the different benchmarks used, our strategy generates an improvement of up to 60% in the call connection rate; of more than 1000% in the ability to connect long-distance calls; and incurs as low as 0.25 of the message overhead.

A Collaborative Multi-Agent Framework for Internet-Based Teleoperation Systems

2013 ◽  
Vol 5 (2) ◽  
pp. 31-54
Author(s):  
Nader Cheaib ◽  
Samir Otmane ◽  
Malik Mallem
Keyword(s):  
Conceptual Model ◽  
Multi Agent Systems ◽  
Collaborative Process ◽  
Agent Systems ◽  
Collaborative Software ◽  
Research Areas ◽  
Multi Agent ◽  
Collaboration Process ◽  
3C Model ◽  
Teleoperation Systems

This paper presents a conceptual model of an agent (called Collaborator Agent) intended to design collaborative software architectures based on multi-agent systems. The authors’ model combines astutely two research areas: Multi-Agent Systems (MAS) and Computer Supported Cooperative Work (CSCW). The particularity of their approach is the division of the collaborative process into three spaces according to Ellis' 3C model: communication, coordination and production. In their work, the authors extend the 3C model by adding a fourth space: collaboration. Hence, the authors present a model based on four types of agents (collaboration, communication, coordination and production) supporting the whole set of collaborative tasks. The model is used to create the conceptual software architecture of their MAS. The authors apply their conceptual model on the ARITI-C system for collaborative online robot teleoperation. Finally, the authors present a quantitative evaluation of the collaboration process in ARITI-C.

Progress in multi-agent systems research

2000 ◽  
Vol 15 (3) ◽  
pp. 285-292
Author(s):  
OMER RANA ◽  
CHRIS PREIST ◽  
MICHAEL LUCK
Keyword(s):  
Interest Group ◽  
Multi Agent Systems ◽  
Hewlett Packard ◽  
Diverse Range ◽  
Agent Based ◽  
Agent Systems ◽  
Systems Research ◽  
Computer Scientists ◽  
Multi Agent ◽  
The Uk

Continuing the series of workshops begun in 1996 (Luck, 1997; Doran et al., 1997; d'Inverno et al., 1997; Fisher et al., 1997) and held in each of the two years since (Luck et al., 1998; Aylett et al., 1998; Binmore et al., 1998; Decker et al., 1999; Beer et al., 1999), the 1999 workshop of the UK Special Interest Group on Multi-Agent Systems (UKMAS'99) took place in Bristol in December. Chaired and organised by Chris Preist of Hewlett Packard Laboratories, with support from both HP and BT Laboratories, the workshop brought together a diverse range of participants, from the agent community in both the UK and abroad, to discuss and present work spanning all areas of agent research. Although dominated by computer scientists, also present at the meeting were electronic engineers, computational biologists, philosophers, sociologists, statisticians, game-theorists, economists and behavioural scientists, with both academia and industry well represented. Indeed, numbers attending these workshops continue to grow, reflecting the continued and rising interest in agent-based systems. The meeting truly demonstrated the wider view of what the term “agency” implied to research in other disciplines and the questions raised at the end of presentations were a pertinent reminder of the diversity of the audience.

scholarly journals Agents and Robots for Reliable Engineered Autonomy:A Perspective from the Organisers of AREA 2020

2021 ◽  
Vol 10 (2) ◽  
pp. 33
Author(s):  
Rafael C. Cardoso ◽  
Angelo Ferrando ◽  
Daniela Briola ◽  
Claudio Menghi ◽  
Tobias Ahlbrecht
Keyword(s):  
Research Trends ◽  
Multi Agent Systems ◽  
Open Problems ◽  
Future Directions ◽  
Agent Systems ◽  
Research Areas ◽  
Multi Agent ◽  
Active Research ◽  
High Level ◽  
First Time

Multi-agent systems, robotics and software engineering are large and active research areas with many applications in academia and industry. The First Workshop on Agents and Robots for reliable Engineered Autonomy (AREA), organised the first time in 2020, aims at encouraging cross-disciplinary collaborations and exchange of ideas among researchers working in these research areas. This paper presents a perspective of the organisers that aims at highlighting the latest research trends, future directions, challenges, and open problems. It also includes feedback from the discussions held during the AREA workshop. The goal of this perspective is to provide a high-level view of current research trends for researchers that aim at working in the intersection of these research areas.

scholarly journals The Word List Distribution in Social Science Research Articles

2017 ◽  
Author(s):  
Arab World English Journal ◽  
Sorawut Chanasattru ◽  
Supong Tangkiengsirisin
Keyword(s):  
Social Science ◽  
Social Science Research ◽  
Word List ◽  
Science Research ◽  
Research Articles ◽  
General Category ◽  
Word Families ◽  
Research Areas ◽  
Flash Cards ◽  
Word Lists

This study investigates the distribution and coverage of words in New General Service List (NGSL) and the Academic Word List (AWL) in social science research articles. Sixty-four open-access English social science research articles published in 2013-2015 in the ScienceDirect General category were selected and compiled to the Social Science Corpus (SSC). The AntWordProfiler 1.4.0 was utilized to calculate the frequency and coverage percentage of words from the two word lists. Word families in level 1 and level 2 of the NGSL were utilized over 70 percent, whilst level 3 word families were used around 60 percent of the entire SSC. Similarly, 99.65 percent of the AWL word families were discovered. Regarding coverage, the NGSL word families accounted for over 70 percent and the AWL word families covered around 14 percent revealing significant coverage of both word lists. The top 10 NGSL word families represented journals subject areas from which they were derived, whilst the top 10 AWL word families were used more repeatedly and linked with social science research areas. The finding of high distributions and coverage corroborated that the NGSL and the AWL significantly contribute to vocabulary pedagogy in preparing students for reading and writing social science research articles. Additionally, some pedagogical implication guidelines of the NGSL and the AWL such as flash cards, quizzes, and written tests were also introduced.

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