Explainable Multi-Agent Systems Through Blockchain Technology

Advances in Artificial Intelligence (AI) are contributing to a broad set of domains. In particular, Multi-Agent Systems (MAS) are increasingly approaching critical areas such as medicine, autonomous vehicles, criminal justice, and financial markets. Such a trend is producing a growing AI-Human socie...

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Published inExplainable, Transparent Autonomous Agents and Multi-Agent Systems Vol. 11763; pp. 41 - 58
Main Authors Calvaresi, Davide, Mualla, Yazan, Najjar, Amro, Galland, Stéphane, Schumacher, Michael
Format Book Chapter Conference Proceeding
LanguageEnglish
Published Switzerland Springer International Publishing AG 2019
Springer International Publishing
SeriesLecture Notes in Computer Science
Subjects
Online AccessGet full text
ISBN303030390X
9783030303907
9783030303914
3030303918
ISSN0302-9743
1611-3349
DOI10.1007/978-3-030-30391-4_3

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Abstract Advances in Artificial Intelligence (AI) are contributing to a broad set of domains. In particular, Multi-Agent Systems (MAS) are increasingly approaching critical areas such as medicine, autonomous vehicles, criminal justice, and financial markets. Such a trend is producing a growing AI-Human society entanglement. Thus, several concerns are raised around user acceptance of AI agents. Trust issues, mainly due to their lack of explainability, are the most relevant. In recent decades, the priority has been pursuing the optimal performance at the expenses of the interpretability. It led to remarkable achievements in fields such as computer vision, natural language processing, and decision-making systems. However, the crucial questions driven by the social reluctance to accept AI-based decisions may lead to entirely new dynamics and technologies fostering explainability, authenticity, and user-centricity. This paper proposes a joint approach employing both blockchain technology (BCT) and explainability in the decision-making process of MAS. By doing so, current opaque decision-making processes can be made more transparent and secure and thereby trustworthy from the human user standpoint. Moreover, several case studies involving Unmanned Aerial Vehicles (UAV) are discussed. Finally, the paper discusses roles, balance, and trade-offs between explainability and BCT in trust-dependent systems.
AbstractList Advances in Artificial Intelligence (AI) are contributing to a broad set of domains. In particular, Multi-Agent Systems (MAS) are increasingly approaching critical areas such as medicine, autonomous vehicles, criminal justice, and financial markets. Such a trend is producing a growing AI-Human society entanglement. Thus, several concerns are raised around user acceptance of AI agents. Trust issues, mainly due to their lack of explainability, are the most relevant. In recent decades, the priority has been pursuing the optimal performance at the expenses of the interpretability. It led to remarkable achievements in fields such as computer vision, natural language processing, and decision-making systems. However, the crucial questions driven by the social reluctance to accept AI-based decisions may lead to entirely new dynamics and technologies fostering explainability, authenticity, and user-centricity. This paper proposes a joint approach employing both blockchain technology (BCT) and explainability in the decision-making process of MAS. By doing so, current opaque decision-making processes can be made more transparent and secure and thereby trustworthy from the human user standpoint. Moreover, several case studies involving Unmanned Aerial Vehicles (UAV) are discussed. Finally, the paper discusses roles, balance, and trade-offs between explainability and BCT in trust-dependent systems.
Author Galland, Stéphane
Schumacher, Michael
Calvaresi, Davide
Mualla, Yazan
Najjar, Amro
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Snippet Advances in Artificial Intelligence (AI) are contributing to a broad set of domains. In particular, Multi-Agent Systems (MAS) are increasingly approaching...
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StartPage 41
SubjectTerms Blockchain
Explainability
Goal-based XAI
MAS
UAV
Title Explainable Multi-Agent Systems Through Blockchain Technology
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