The paper introduces an optimization framework for AI agents to strategically seek support, proving a threshold policy on support value and providing an online algorithm to control missed-support error without distributional assumptions.
Learning paradigms for hybrid decision-making systems.ACM Comput
2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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2026 2verdicts
UNVERDICTED 2representative citing papers
Exploratory mixed-methods research identifying user expectations for positive UX with AI agents in business and informing a follow-up survey experiment.
citing papers explorer
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Strategic Decision Support for AI Agents
The paper introduces an optimization framework for AI agents to strategically seek support, proving a threshold policy on support value and providing an online algorithm to control missed-support error without distributional assumptions.
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Human-AI Agent Interaction in a Business Context
Exploratory mixed-methods research identifying user expectations for positive UX with AI agents in business and informing a follow-up survey experiment.