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

2011 ◽  
pp. 132-153
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.

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.

scholarly journals Can models of agents be transferred between different areas?

2000 ◽  
Vol 15 (2) ◽  
pp. 197-203 ◽  
Author(s):  
RUTH AYLETT ◽  
KERSTIN DAUTENHAHN ◽  
JIM DORAN ◽  
MICHAEL LUCK ◽  
SCOTT MOSS ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Computer Science ◽  
Multi Agent Systems ◽  
Ongoing Research ◽  
Agent Based ◽  
Agent Systems ◽  
Sustained Activity ◽  
Diverse Environment ◽  
The World ◽  
Multi Agent

One of the main reasons for the sustained activity and interest in the field of agent-based systems, apart from the obvious recognition of its value as a natural and intuitive way of understanding the world, is its reach into very many different and distinct fields of investigation. Indeed, the notions of agents and multi-agent systems are relevant to fields ranging from economics to robotics, in contributing to the foundations of the field, being influenced by ongoing research, and in providing many domains of application. While these various disciplines constitute a rich and diverse environment for agent research, the way in which they may have been linked by it is a much less considered issue. The purpose of this panel was to examine just this concern, in the relationships between different areas that have resulted from agent research. Informed by the experience of the participants in the areas of robotics, social simulation, economics, computer science and artificial intelligence, the discussion was lively and sometimes heated.

scholarly journals Rational verification: game-theoretic verification of multi-agent systems

2021 ◽  
Author(s):  
Alessandro Abate ◽  
Julian Gutierrez ◽  
Lewis Hammond ◽  
Paul Harrenstein ◽  
Marta Kwiatkowska ◽  
...  
Keyword(s):  
Computer Science ◽  
Temporal Logic ◽  
State Of The Art ◽  
Multi Agent System ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
The Past ◽  
Multi Agent ◽  
Game Theoretic ◽  
Temporal Logic Formula

AbstractWe provide a survey of the state of the art of rational verification: the problem of checking whether a given temporal logic formula ϕ is satisfied in some or all game-theoretic equilibria of a multi-agent system – that is, whether the system will exhibit the behavior ϕ represents under the assumption that agents within the system act rationally in pursuit of their preferences. After motivating and introducing the overall framework of rational verification, we discuss key results obtained in the past few years as well as relevant related work in logic, AI, and computer science.

scholarly journals Information Retrieval in Business

2021 ◽  
Author(s):  
Revati Wable
Keyword(s):  
Information Retrieval ◽  
Computer Science ◽  
Research Paper ◽  
Research Area ◽  
Important Research ◽  
Important Research Area

For several years people have realized the importance of archiving and finding information. With the need of computers, finding useful information from such collections has become a necessity. Information retrieval has become an important research area in the field of computer science and gained importance in several fields like business, healthcare, agriculture, medicine, law and many other fields. Information retrieval is finding material that could be in the form of a document consisting of unstructured nature that provides the required information. This research paper focuses on the need, models and the processes involved in information retrieval. A case study on INSYDER system has been proposed to gain holistic knowledge of information retrieval in the field of business.

MAgICS

2011 ◽  
pp. 1-25 ◽  
Author(s):  
Forrest Stonedahl ◽  
Michelle Wilkerson-Jerde ◽  
Uri Wilensky
Keyword(s):  
Computer Science ◽  
Science Classroom ◽  
Multi Agent Systems ◽  
Design Strategies ◽  
Agent Systems ◽  
Preliminary Version ◽  
Multi Agent ◽  
Upper Level ◽  
Deep Integration ◽  
Science Framework

The authors present a preliminary version of the MAgICS (Multi-Agent Introduction to Computer Science) framework, which is a new approach for revitalizing introductory undergraduate or high school computer science curricula through the deep integration of agent-based modeling (ABM) and multi-agent systems (MAS) perspectives. The authors discuss the merits of using multi-agent systems as a lens for conceptual understanding across disciplines, compare multi-agent approaches to traditional serial ones, and explore how this approach can bring together disparate topics in computer science through the common focus on emergent systems to promote a broader view of the field as a whole. To exemplify this approach, they have developed a suite of curricular models for topics spanning from searching and sorting to machine learning and networks and security. By introducing these topics with a focus on parallel, distributed, and stochastic methods, they can make traditionally upper-level topics both motivating and accessible to introductory-level students. The authors review findings from a short implementation of several elements of MAgICS in an introductory computer science classroom with regard to student motivation and evidence of learning of distributed design strategies.

EARTHQUAKE TIME PREDICTION WITH MULTI-AGENT SYSTEMS

2020 ◽  
Vol 69 (1) ◽  
pp. 275-279
Author(s):  
A.A. Abyurova ◽  
Keyword(s):  
Time Series ◽  
Regression Models ◽  
Research Area ◽  
Seismic Signals ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Time Prediction ◽  
Python Programming Language ◽  
Multi Agent ◽  
Python Programming

This article is devoted to the development of multi-agent systems for predicting the time of earthquakes based on seismic signals. The work uses a dataset from laboratory signals, which used to calculate the time predicted before the next earthquake. The MadKIT platform and the Python programming language are used to build multi-agent systems. The "tsfresh" package is used to calculate a large number of time series characteristics, so-called features, from seismic signals for further use in regression. The article considers one of the regression models - LightGBM. Using it, a set of data was processed and the predicted time of the earthquake was obtained. This article shows the relevance and prospects of the research area, describes the functionality of the created agents

Analysis and synthesis: multi-agent systems in the social sciences

2012 ◽  
Vol 27 (2) ◽  
pp. 123-136 ◽  
Author(s):  
Robert E. Marks
Keyword(s):  
Social Sciences ◽  
Computer Science ◽  
Common Source ◽  
Multi Agent Systems ◽  
Agent Based ◽  
Agent Systems ◽  
The Social ◽  
Analysis And Synthesis ◽  
Multi Agent ◽  
Computational Systems

AbstractAlthough they flow from a common source, the uses of multi-agent systems (or ‘agent-based computational systems’––ACE) vary between the social sciences and computer science. The distinction can be broadly summarized as analysis versus synthesis, or explanation versus design. I compare and contrast these uses, and discuss sufficiency and necessity in simulations in general and in multi-agent systems in particular, with a computer science audience in mind.

scholarly journals Dialogue Games in Multi-Agent Systems

2001 ◽  
Vol 22 (3) ◽  
Author(s):  
Peter McBurney ◽  
Simon Parsons
Keyword(s):  
Artificial Intelligence ◽  
Computer Science ◽  
Multi Agent Systems ◽  
Dialogue Games ◽  
Agent Systems ◽  
Open Research ◽  
Multi Agent ◽  
Research Questions ◽  
The Many ◽  
Formal Dialogue

Formal dialogue games have been studied in philosophy since at least the time of Aristotle. Recently they have been applied in various contexts in computer science and artificial intelligence, particularly as the basis for interaction between autonomous software agents. We review these applications and discuss the many open research questions and challenges at this exciting interface between philosophy and computer science.

FuzzyOrganization of Self-Adaptive Agents Based On Software Components

2014 ◽  
Vol 10 (3) ◽  
pp. 36-56 ◽  
Author(s):  
Abderrahim Siam ◽  
Ramdane Maamri ◽  
Zaïdi Sahnoun
Keyword(s):  
Membership Function ◽  
Software Components ◽  
Automatic Assembly ◽  
Multi Agent Systems ◽  
Adaptive Agents ◽  
Agent Systems ◽  
Proposed Model ◽  
Multi Agent ◽  
The Membership Function ◽  
Self Adaptive

This paper addresses the development of organizational multi agent systems as a preferred solution to develop open, distributed and adaptive application. It proposes a combination between components and agents to define a flexible organizational model of MAS based on three concepts: roles, self-adaptive agents based on components and fuzzy groups. Roles are played by agents in fuzzy groups. A fuzzy group is a fuzzy set of agents characterized by a membership function expressing the partial membership of each agent to the group. The membership function expresses the degree of capacity of each agent to play a role. This work proposes a fuzzy measure of the capacity of agents to play roles. It proposes a model of auto adaptive agents constructed by automatic assembly (reassembly) of software components. Components implement required capabilities to play roles. The proposed model and introduced concepts have been tested using the Madkit platform.

Introducing Multiagent Systems to Undergraduates through Games and Chocolate

2011 ◽  
pp. 101-114 ◽  
Author(s):  
Emma Bowring ◽  
Milind Tambe
Keyword(s):  
Science Fiction ◽  
Computer Science ◽  
Lessons Learned ◽  
Special Topic ◽  
Science Students ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Big Picture ◽  
Multi Agent ◽  
Multi Agents

The field of “intelligent agents and multi-agent systems” is maturing; no longer is it a special topic to be introduced to graduate students after years of training in computer science and many introductory courses in artificial intelligence. Instead, the time is ripe to introduce agents and multi-agents directly to undergraduate students, whether majoring in computer science or not. This chapter focuses on exactly this challenge, drawing on the co-authors’ experience of teaching several such undergraduate courses on agents and multi-agents, over the last three years at two different universities. The chapter outlines three key issues that must be addressed. The first issue is facilitating students’ intuitive understanding of fundamental concepts of multi-agent systems; the authors illustrate uses of science fiction materials and classroom games to not only provide students with the necessary intuitive understanding but with the excitement and motivation for studying multi-agent systems. The second is in selecting the right material — either science-fiction material or games — for providing students the necessary motivation and intuition; we outline several criteria that have been useful in selecting such material. The third issue is in educating students about the fundamental philosophical, ethical and social issues surrounding agents and multi-agent systems:they outline course materials and classroom activities that allow students to obtain this “big picture” futuristic vision of our science. The authors conclude with feedback received, lessons learned and impact on both the computer science students and non computer-science students.

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