Argument & Computation
Scope & Guideline
Innovating the Future of Argumentation and AI
Introduction
Aims and Scopes
- Formal Argumentation Models:
The journal publishes research on the development and analysis of formal models of argumentation, exploring various semantics, frameworks, and methodologies for representing and reasoning about arguments. - Computational Approaches to Argumentation:
This area encompasses studies that apply computational techniques to argumentation, including algorithms for learning argumentation frameworks, analyzing argument strength, and developing AI systems that engage in argumentative dialogue. - Interdisciplinary Applications:
Research often explores the application of argumentation theory across disciplines, such as law, healthcare, and ethics, fostering collaboration between computer science, philosophy, and social sciences. - Ethics and Argumentation:
The journal highlights the role of ethical considerations in argumentation, examining how arguments are constructed and evaluated in contexts like healthcare, environmental policy, and AI ethics. - Dialogue and Interaction in Argumentation:
This focus area includes studies on argumentation in dialogue systems, exploring how agents can engage in persuasive and strategic argumentation to achieve specific goals.
Trending and Emerging
- Ethical Argumentation in AI:
There is a growing focus on the ethical implications of argumentation in AI systems, exploring how AI-generated arguments can be assessed for quality and moral considerations, which is crucial in the context of increasing reliance on AI in decision-making. - Learning from Argumentation Data:
The trend of using machine learning techniques to analyze and learn from argumentation data is on the rise, indicating a shift towards data-driven approaches that can enhance the understanding of argument dynamics and effectiveness. - Argumentation in Legal Contexts:
Research exploring argumentation frameworks within legal reasoning is becoming more prominent, reflecting the need for robust models that can handle complex legal scenarios and improve legal decision-making processes. - Explainable AI and Argumentation:
There is an increasing interest in the intersection of explainable AI and argumentation, focusing on how argumentation can contribute to transparency and accountability in AI systems, particularly in high-stakes applications. - Community Detection in Argumentation:
Emerging studies on community detection through argument similarity indicate a trend towards understanding how arguments are formed and perceived within social networks and online debates, highlighting the relevance of argumentation in digital communication.
Declining or Waning
- Classic Argumentation Schemes:
Research centered on traditional argumentation schemes has seen a decrease, possibly due to the emergence of more sophisticated models and frameworks that incorporate dynamic and computational elements. - Historical and Philosophical Foundations:
Although foundational theories remain important, there is less emphasis on purely historical or philosophical discussions of argumentation, as the journal increasingly prioritizes empirical and computational studies. - Generalized Argumentation Frameworks:
There appears to be a waning interest in generalized frameworks that do not incorporate specific applications or computational methods, as researchers are gravitating towards more specialized and practical implementations.
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