3 articles tagged with #bounded-rationality. AI-curated summaries with sentiment analysis and key takeaways from 50+ sources.
Researchers present Bounded Pragmatic Listener (BPL), a Bayesian framework that models how cognitive limitations affect susceptibility to misinformation. The framework incorporates three cognitively grounded constraints—working memory limits, information bottlenecks, and saliency-weighted sampling—to predict vulnerability to disinformation across benchmark datasets.
The article explores incentive-compatibility in cryptoeconomic algorithms, examining how bounded rationality affects the design of blockchain consensus mechanisms, reputation systems, and trading processes. It discusses the challenges of creating systems where participants' optimal strategies align with desired network outcomes.
Researchers present the Artificial Agency Program (AAP), a framework for developing AI systems as resource-bounded agents driven by curiosity and learning progress under physical constraints. The program aims to create AI that enhances human capabilities through better sensing, understanding, and action while reducing interface friction between people, tools, and environments.
