Coordination, Cooperation and Conflict Resolution in Multi-Agent Systems

Alshabi, W.; Ramaswamy, Srini; Itmi, Mhamed; Abdulrab, Habib

doi:10.1007/978-1-4020-6268-1_87

Cited by 16 publications

(6 citation statements)

References 50 publications

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“…[6]. 2 An important aspect of this model is an agent's InteractionMatrix, which stores information (relationship values) about the agents' interaction experiences with other agents, initially being zero-based and increasing or decreasing depending on interpersonal experience. When an agent receives any amount of food from another agent, its relationship value with the sharing agent is increased.…”

Section: B Types Of Agents and Their Characteristicsmentioning

confidence: 99%

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Agent-Based Modelling of Primitive Human Communities

Jahanbazi

Frantz

Purvis

et al. 2014

2014 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT)

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The task of tracing what underlies the transition from kinship tribes to nation states continues to remain an important challenge for interdisciplinary study. Multi-agent simulation can shed light on these evolutionary processes by examining the emergent social behaviour that arises from individual agent interactions. In this paper, we build a model based on existing observational and simulation studies of pre-contact Pacific Island hunter-gatherer societies. Starting with the simple tribal structure, we examine how different societies' structures were affected by various characteristics and strategies of their chiefs. Our model represents the influence of societies' structure on how agents fulfil their basic needs and the consequences of an agent's action on both short term and long term society's survival. The evolving societal structures of the model have long-term effects on wealth inequality and whether the society grows or collapses. The results of an extensive model exploration encourage the idea that significantly different outcomes in social welfare do not necessarily require massive changes to all the agents, but can be achieved by relatively moderate modifications in social structure and the governance of societies.

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Section: B Types Of Agents and Their Characteristicsmentioning

confidence: 99%

“…Numerous studies in the field of agent-based social simulation' have revealed the effectiveness of agent-based modelling for addressing social complexities (e.g. [1] [2] [3] [4]). The work presented here uses agent-based modelling to develop a deeper understanding of pre-Western-contact Pacific Island.…”

Section: Introductionmentioning

confidence: 99%

Agent-Based Modelling of Primitive Human Communities

Jahanbazi

Frantz

Purvis

et al. 2014

2014 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT)

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“…We plan to extend the approach to fully automate user environments in our future work. The subject of conflict-resolution among agents has been well-researched [39,40]. Liu et al [41] classified conflicts among agents into three categories: beliefs conflicts, goals conflicts, and plans conflicts.…”

Section: Related Workmentioning

confidence: 99%

An Agent-Based Approach to Realize Emergent Configurations in the Internet of Things

2020

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The Internet of Things (IoT) has enabled physical objects and devices, often referred to as things, to connect and communicate. This has opened up for the development of novel types of services that improve the quality of our daily lives. The dynamicity and uncertainty of IoT environments, including the mobility of users and devices, make it hard to foresee at design time available things and services. Further, users should be able to achieve their goals seamlessly in arbitrary environments. To address these challenges, we exploit Artificial Intelligence (AI) to engineer smart IoT systems that can achieve user goals and cope with the dynamicity and uncertainty of their environments. More specifically, the main contribution of this paper is an approach that leverages the notion of Belief-Desire-Intention agents and Machine Learning (ML) techniques to realize Emergent Configurations (ECs) in the IoT. An EC is an IoT system composed of a dynamic set of things that connect and cooperate temporarily to achieve a user goal. The approach enables the distributed formation, enactment, adaptation of ECs, and conflict resolution among them. We present a conceptual model of the entities of the approach, its underlying processes, and the guidelines for using it. Moreover, we report about the simulations conducted to validate the feasibility of the approach and evaluate its scalability.

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“…As A does not only consider its own goals, but also the ones of B, one can regard A as empathic, following Coplan's definition of empathy, as "a process through which an observer simulates another's situated psychological states, while maintaining clear self-other differentiation" [12]. While existing literature covers conflict resolution in multi-agent systems from a broad range of perspectives (see for a partial overview: [2]), devising a theoretical framework for autonomous agents that consider the utility functions (or preferences) of agents in their environment and use a combined utilitarian/rule-based approach to identify and resolve conflicts of interests can be considered a novel idea. However, existing multi-agent systems research can be leveraged to implement core components of such a framework, as is discussed later.…”

Section: Background and Problem Descriptionmentioning

confidence: 99%

Empathic Autonomous Agents

Kampik¹,

Nieves²,

Lindgren³

2019

Preprint

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Identifying and resolving conflicts of interests is a key challenge when designing autonomous agents. For example, such conflicts often occur when complex information systems interact persuasively with humans and are in the future likely to arise in non-human agent-to-agent interaction. We introduce a theoretical framework for an empathic autonomous agent that proactively identifies potential conflicts of interests in interactions with other agents (and humans) by considering their utility functions and comparing them with its own preferences using a system of shared values to find a solution all agents consider acceptable. To illustrate how empathic autonomous agents work, we provide running examples and a simple prototype implementation in a general-purpose programing language. To give a high-level overview of our work, we propose a reasoning-loop architecture for our empathic agent.Keywords: Multi-agent systems • Utility theory • Conflicts of interests 1 E.g., research provides evidence that contextual advertisement influences how users process online news [25]; social network applications have effectively been employed for political persuasion (see for an example: [4].

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Coordination, Cooperation and Conflict Resolution in Multi-Agent Systems

Cited by 16 publications

References 50 publications

Agent-Based Modelling of Primitive Human Communities

Agent-Based Modelling of Primitive Human Communities

An Agent-Based Approach to Realize Emergent Configurations in the Internet of Things

Empathic Autonomous Agents

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