Publication detail

Multi-Agent Experimental Framework with Hierarchical Model of Trust in Contexts for Decision Making

SAMEK, J. MALAČKA, O. ZBOŘIL, F. HANÁČEK, P.

Original Title

Multi-Agent Experimental Framework with Hierarchical Model of Trust in Contexts for Decision Making

English Title

Multi-Agent Experimental Framework with Hierarchical Model of Trust in Contexts for Decision Making

Type

conference paper

Language

en

Original Abstract

The research in the area of computational models based on trust or reputation is a recent discipline and a lot of work and theoretical approaches was done. But only few computational trust and reputation models directly include ability to work with multi-context property of trust. Moreover, experimental frameworks or tested for theoretical computational are very sporadic. In our recent research, we provide two interoperable solutions which are able together cover a wide range of fundamental problems in trust and reputation computational models such as: single- and multi-context trust model, ability to work with uncertainty and recommendation, reputation and decision making protocol. In order to verify these proposal, we implemented an robust experimental framework based on multi-agent paradigms. In this paper, we describe one part of many simulation scenarios, which is focused on comparison single- and multi-context approach to trust.

English abstract

The research in the area of computational models based on trust or reputation is a recent discipline and a lot of work and theoretical approaches was done. But only few computational trust and reputation models directly include ability to work with multi-context property of trust. Moreover, experimental frameworks or tested for theoretical computational are very sporadic. In our recent research, we provide two interoperable solutions which are able together cover a wide range of fundamental problems in trust and reputation computational models such as: single- and multi-context trust model, ability to work with uncertainty and recommendation, reputation and decision making protocol. In order to verify these proposal, we implemented an robust experimental framework based on multi-agent paradigms. In this paper, we describe one part of many simulation scenarios, which is focused on comparison single- and multi-context approach to trust.

Keywords

trust; trust modelling; single-context trust; multi-context trust; HMTC; confidence interval

RIV year

2011

Released

05.09.2011

Publisher

Department of Intelligent Systems FIT BUT

Location

Brno

ISBN

978-80-214-4320-4

Book

Proceeding of the 2nd International Conference on Computer Modelling and Simulation

Edition

NEUVEDEN

Edition number

NEUVEDEN

Pages from

128

Pages to

136

Pages count

9

BibTex


@inproceedings{BUT76365,
  author="Jan {Samek} and Ondřej {Malačka} and František {Zbořil} and Petr {Hanáček}",
  title="Multi-Agent Experimental Framework with Hierarchical Model of Trust in Contexts for Decision Making",
  annote="The research in the area of computational models based on trust or reputation is
a recent discipline and a lot of work and theoretical approaches was done. But
only few computational trust and reputation models directly include ability to
work with multi-context property of trust. Moreover, experimental frameworks or
tested for theoretical computational are very sporadic. In our recent research,
we provide two interoperable solutions which are able together cover a wide range
of fundamental problems in trust and reputation computational models such as:
single- and multi-context trust model, ability to work with uncertainty and
recommendation, reputation and decision making protocol. In order to verify these
proposal, we implemented an robust experimental framework based on multi-agent
paradigms. In this paper, we describe one part of many simulation scenarios,
which is focused on comparison single- and multi-context approach to trust.",
  address="Department of Intelligent Systems FIT BUT",
  booktitle="Proceeding of the 2nd International Conference on Computer Modelling and Simulation",
  chapter="76365",
  edition="NEUVEDEN",
  howpublished="electronic, physical medium",
  institution="Department of Intelligent Systems FIT BUT",
  year="2011",
  month="september",
  pages="128--136",
  publisher="Department of Intelligent Systems FIT BUT",
  type="conference paper"
}