Table of Contents
Fetching ...

Trust from Ethical Point of View: Exploring Dynamics Through Multiagent-Driven Cognitive Modeling

Abbas Tariverdi

TL;DR

The paper examines how rationality and morality frame ethical trust and distinguishes trust from trustworthiness. It advances a computational approach using an agent-based cognitive simulation in disaster-response contexts, where Emotional Agents powered by Plutchik's Wheel, memory, and social dynamics allocate scarce resources. The work operationalizes theoretical foundations with components like cognitive load, Big Five traits, feedback, and external events to reveal how trust networks form and evolve under stress. It provides a robust, adaptable framework for studying trust in socio-technical systems and offers GitHub resources for implementation.

Abstract

The paper begins by exploring the rationality of ethical trust as a foundational concept. This involves distinguishing between trust and trustworthiness and delving into scenarios where trust is both rational and moral. It lays the groundwork for understanding the complexities of trust dynamics in decision-making scenarios. Following this theoretical groundwork, we introduce an agent-based simulation framework that investigates these dynamics of ethical trust, specifically in the context of a disaster response scenario. These agents, utilizing emotional models like Plutchik's Wheel of Emotions and memory learning mechanisms, are tasked with allocating limited resources in disaster-affected areas. The model, which embodies the principles discussed in the first section, integrates cognitive load management, Big Five personality traits, and structured interactions within networked or hierarchical settings. It also includes feedback loops and simulates external events to evaluate their impact on the formation and evolution of trust among agents. Through our simulations, we demonstrate the intricate interplay of cognitive, emotional, and social factors in ethical decision-making. These insights shed light on the behaviors and resilience of trust networks in crisis situations, emphasizing the role of rational and moral considerations in the development of trust among autonomous agents. This study contributes to the field by offering an understanding of trust dynamics in socio-technical systems and by providing a robust, adaptable framework capable of addressing ethical dilemmas in disaster response and beyond. The implementation of the algorithms presented in this paper is available at this GitHub repository: \url{https://github.com/abbas-tari/ethical-trust-cognitive-modeling}.

Trust from Ethical Point of View: Exploring Dynamics Through Multiagent-Driven Cognitive Modeling

TL;DR

The paper examines how rationality and morality frame ethical trust and distinguishes trust from trustworthiness. It advances a computational approach using an agent-based cognitive simulation in disaster-response contexts, where Emotional Agents powered by Plutchik's Wheel, memory, and social dynamics allocate scarce resources. The work operationalizes theoretical foundations with components like cognitive load, Big Five traits, feedback, and external events to reveal how trust networks form and evolve under stress. It provides a robust, adaptable framework for studying trust in socio-technical systems and offers GitHub resources for implementation.

Abstract

The paper begins by exploring the rationality of ethical trust as a foundational concept. This involves distinguishing between trust and trustworthiness and delving into scenarios where trust is both rational and moral. It lays the groundwork for understanding the complexities of trust dynamics in decision-making scenarios. Following this theoretical groundwork, we introduce an agent-based simulation framework that investigates these dynamics of ethical trust, specifically in the context of a disaster response scenario. These agents, utilizing emotional models like Plutchik's Wheel of Emotions and memory learning mechanisms, are tasked with allocating limited resources in disaster-affected areas. The model, which embodies the principles discussed in the first section, integrates cognitive load management, Big Five personality traits, and structured interactions within networked or hierarchical settings. It also includes feedback loops and simulates external events to evaluate their impact on the formation and evolution of trust among agents. Through our simulations, we demonstrate the intricate interplay of cognitive, emotional, and social factors in ethical decision-making. These insights shed light on the behaviors and resilience of trust networks in crisis situations, emphasizing the role of rational and moral considerations in the development of trust among autonomous agents. This study contributes to the field by offering an understanding of trust dynamics in socio-technical systems and by providing a robust, adaptable framework capable of addressing ethical dilemmas in disaster response and beyond. The implementation of the algorithms presented in this paper is available at this GitHub repository: \url{https://github.com/abbas-tari/ethical-trust-cognitive-modeling}.
Paper Structure (13 sections, 8 figures)

This paper contains 13 sections, 8 figures.

Figures (8)

  • Figure 1: Average Opinions Over Time in a Disaster Response Scenario.
  • Figure 2: Average Trust Over Time in a Disaster Response Scenario.
  • Figure 3: Dynamics of Average Emotions Over Time Among Agents, including an emotional representation of trust.
  • Figure 4: Interplay of Average Opinions and Trust Over Time with Key Event Annotations.
  • Figure 5: Social Network Diagrams representing the relationships and influence dynamics among agents. Figure \ref{['fig:sub1']} maps the friendship connections, while Figure \ref{['fig:sub2']} details the influence network, with node sizes representing agents' influence levels.
  • ...and 3 more figures