This article presents a Bayesian approach to off-policy evaluation (OPE) and off-policy learning (OPL) for large action spaces. The authors propose a unified Bayesian framework, sDM, that leverages action correlations…
Continue readingThe article by Ruqing Xu discusses the design of an algorithm that aids in decision making. It contemplates whether to act directly based on the algorithm’s prediction or delegate the…
Continue readingThe rapid progress of foundation models has led to the prosperity of autonomous agents, which leverage the universal capabilities of these models for reasoning, decision-making, and environmental interaction. However, these…
Continue readingDespite various countermeasures, people continue to fall for phishing emails. This paper presents an empirical study that investigates how people make decisions when responding to emails. The study identifies different…
Continue readingThis article delves into the application of game theory in studying cyber attacker and defender behaviors. It critiques the inherent limitations due to game theory’s roots in economics where players…
Continue readingThe paper presents a new approach to make Explainable Artificial Intelligence (XAI) more accessible to a wider audience, including non-experts. The researchers developed a Large Language Model (LLM) using ChatGPT…
Continue readingThe paper provides a systematic literature review of 57 papers to understand the use of decision-making algorithms in homelessness research. It highlights the increasing use of data-driven models by government…
Continue readingThe article explores the gap between the information provided by AI systems and the information needs of people affected by algorithmic decision-making. It introduces the ‘XAI Novice Question Bank’, a…
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