Abstract

Selecting a suitable conflict resolution strategy when conflicts appear in multi-agent environments is a hard problem. There is a need to formulate a model for strategic decision making in selecting a strategy to resolve conflicts. In this paper, we formalise a model for selecting a conflict resolution strategy in multi-agent systems. The model is expected to select a suitable strategy which guaranties low cost in terms of the number of messages and time ticks. This paper focuses on a novel method to guide strategic decision making for conflict resolution. The proposed model is named as Conflict Resolution Strategy Selection Method (ConfRSSM). We identified three distinct types of intervention: (1) domain requirement, (2) conflict strength, and (3) confidence level of the conflicting agents. We also ascertain that the most appropriate conflict resolution strategy for a given conflict depends on the type of conflict (weak, strong), the agents’ confidence level, and the domain preferences. Our method explores the best strategic choices that will reduce the cost and time in selecting a strategy.

Highlights

  • When agents work as a team, in the environments of multiagent, and a conflict state appears among them, there is a need to select one of the multiple strategies to resolve the conflict

  • Current conflict resolution literature on resolving conflict is deficient in four major areas: (1) There is no clear attention to a confidence level of conflicting agents’ opinions and the effects of these levels on the conflict outcome, (2) There is no attention to the number of conflicting agents and number of issues that agents conflicts about it, (3) There is no suggestion of ignoring some unimportant conflict states using submitting strategy to enhance the conflict resolution process, and (4) There are no rules to select an appropriate strategy to solve conflicts that guaranty less cost and time

  • We proposed that an agent must have ability to select an appropriate conflict resolution strategy, according to: the strength of conflicts (e.g. Weak conflict, or strong conflict), the agent’s confidence level in their opinions (e.g. High level opinion's confidence, and low level opinion's confidence)

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Summary

INTRODUCTION

When agents work as a team, in the environments of multiagent, and a conflict state appears among them, there is a need to select one of the multiple strategies to resolve the conflict. If any conflict state among agents resolved by negotiation strategy that requires many messages, this may lead to a heavy coordination state. Based on this introduction, there is a real need to include some strategies that ignore some unimportant conflict states or include submitting strategy to enhance the performance the conflict resolution method. Current conflict resolution literature on resolving conflict is deficient in four major areas: (1) There is no clear attention to a confidence level of conflicting agents’ opinions and the effects of these levels on the conflict outcome, (2) There is no attention to the number of conflicting agents (number of groups) and number of issues that agents (groups) conflicts about it, (3) There is no suggestion of ignoring some unimportant conflict states using submitting strategy to enhance the conflict resolution process, and (4) There are no rules to select an appropriate strategy to solve conflicts that guaranty less cost and time. We proposed that an agent must have ability to select an appropriate conflict resolution strategy, according to: the strength of conflicts (e.g. Weak conflict, or strong conflict), the agent’s confidence level in their opinions (e.g. High level opinion's confidence, and low level opinion's confidence)

RELATED WORK
Conflicts in Multi-agent Systems
State-of-the-art in Conflict Resolution
Conflict Resolution Strategy Selection
Limitations
RESEARCH BACKGROUND AND FOCUS
FORMALISING CONFRSSM DESIGN COMPONENTS
Definitions of ConfRSSM Components
CONFLICT RESOLUTION STRATEGY SELECTION METHOD
Conflict Resolution Strategies
THE CRSSA ARCHITECTURE
Strategies Characteristics Analysis
Findings
CONCLUSION AND FUTURE WORK
Full Text
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