AI agents can take actions. At times, those actions can go beyond what is intended. Agent reliability can be defined as assurance that an agent will stay within intended bounds and operate within limits. Today, there is no shared framework or language for describing, validating, and benchmarking the reliability of agen...
Mike Hsu, Medha Bankhwal, Béatrice Moissinac et al.· 0 citations
This paper presents the first systematic empirical study in the financial domain to characterize how an adversarial signal enters a multi-agent trading system and how far it survives toward the decision, and evaluates four communication topologies under data- and agent-level attacks.
CheolWon Na, Hao Ni, Lukasz Szpruch et al.· 0 citations
This report argues that affirmative AI coverage with limits in the billions is achievable by 2030, but only with industry-wide coordination, and lays out an eight-component AI insurance stack spanning incident data collection, catastrophe modeling, standards, contract design, risk selection, pricing, monitoring, and cl...
Cristian Trout, Sanmi Koyejo, S. Romanosky et al.· arXiv.org· 0 citations
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