TRUST MANAGEMENT THROUGH FUZZY REPUTATION

2003 ◽  
Vol 12 (01) ◽  
pp. 135-155 ◽  
Author(s):  
J. CARBO ◽  
J. M. MOLINA ◽  
J. DAVILA
Keyword(s):  
Fuzzy Sets ◽  
Trust Management ◽  
General Situation ◽  
Uncertain Information ◽  
Multi Agent Systems ◽  
Management Mechanism ◽  
Potential Benefits ◽  
Multi Agent ◽  
Reputation Mechanisms ◽  
Significant Factors

Open electronic communities may bring together people geographically and culturally unrelated to each other. In this context, taking costly decisions depends on the expectations created according to past behaviour of others. This kind of information is usually called reputation and it is one of the most significant factors to trust merchants and recommenders in electronic commerce interactions. When agents are acting on behalf of humans in such commercial scenarios, they should represent and reason about trust and reputation as humans do. In this paper a trust management mechanism tackles the vague, subjective and uncertain information about others using fuzzy sets. The operations defined over such fuzzy sets updates the reputation of merchants according to the general situation faced. This trust management mechanism is applied to a multiagent system of merchants, recommenders and buyers, where collaborative recommendations coexist with competitive intentions. The developed multi-agent system is used to compare the level of success of predictions obtained from the fuzzy computations with some of the most well known (crisp) reputation mechanisms: ebay, bizrate, sporas and regret when the behaviour of merchants change in different degrees. Finally, the potential benefits of using fuzzy sets to manage reputation in multi-agent systems are analyzed according to the excellent experimental results shown.

scholarly journals A HYBRID MODEL FOR SHARING INFORMATION BETWEEN FUZZY, UNCERTAIN AND DEFAULT REASONING MODELS IN MULTI-AGENT SYSTEMS

2002 ◽  
Vol 10 (04) ◽  
pp. 401-450 ◽  
Author(s):  
XUDONG LUO ◽  
CHENGQI ZHANG ◽  
NICHOLAS R. JENNINGS
Keyword(s):  
Hybrid Model ◽  
Approximate Reasoning ◽  
Default Reasoning ◽  
Uncertain Reasoning ◽  
Uncertain Information ◽  
Multi Agent Systems ◽  
Unified Framework ◽  
Agent Systems ◽  
Special Cases ◽  
Multi Agent

This paper develops a hybrid model which provides a unified framework for the following four kinds of reasoning: 1) Zadeh's fuzzy approximate reasoning; 2) truth-qualification uncertain reasoning with respect to fuzzy propositions; 3) fuzzy default reasoning (proposed, in this paper, as an extension of Reiter's default reasoning); and 4) truth-qualification uncertain default reasoning associated with fuzzy statements (developed in this paper to enrich fuzzy default reasoning with uncertain information). Our hybrid model has the following characteristics: 1) basic uncertainty is estimated in terms of words or phrases in natural language and basic propositions are fuzzy; 2) uncertainty, linguistically expressed, can be handled in default reasoning; and 3) the four kinds of reasoning models mentioned above and their combination models will be the special cases of our hybrid model. Moreover, our model allows the reasoning to be performed in the case in which the information is fuzzy, uncertain and partial. More importantly, the problems of sharing the information among heterogeneous fuzzy, uncertain and default reasoning models can be solved efficiently by using our model. Given this, our framework can be used as a basis for information sharing and exchange in knowledge-based multi-agent systems for practical applications such as automated group negotiations. Actually, to build such a foundation is the motivation of this paper.

scholarly journals A computational model of argumentation schemes for multi-agent systems

2021 ◽  
pp. 1-39
Author(s):  
Alison R. Panisson ◽  
Peter McBurney ◽  
Rafael H. Bordini
Keyword(s):  
Decision Making ◽  
Autonomous Agents ◽  
Uncertain Information ◽  
Application Domain ◽  
Argumentation Schemes ◽  
Multi Agent Systems ◽  
Argumentation Framework ◽  
Agent Communication ◽  
Agent Systems ◽  
Multi Agent

There are many benefits of using argumentation-based techniques in multi-agent systems, as clearly shown in the literature. Such benefits come not only from the expressiveness that argumentation-based techniques bring to agent communication but also from the reasoning and decision-making capabilities under conditions of conflicting and uncertain information that argumentation enables for autonomous agents. When developing multi-agent applications in which argumentation will be used to improve agent communication and reasoning, argumentation schemes (reasoning patterns for argumentation) are useful in addressing the requirements of the application domain in regards to argumentation (e.g., defining the scope in which argumentation will be used by agents in that particular application). In this work, we propose an argumentation framework that takes into account the particular structure of argumentation schemes at its core. This paper formally defines such a framework and experimentally evaluates its implementation for both argumentation-based reasoning and dialogues.

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