Prior-Agnostic Robust Forecast Aggregation
Robust forecast aggregation combines the predictions of multiple information sources to perform well in the worst case across all possible information structures. Previous work largely focuses on settings with a known binary state space, where the state is either 0 or 1. We study prior-agnostic robust forecast aggregation in which the aggregator observes only experts' reports, yet is ignorant of both the underlying joint information structure and the full prior, including the underlying state space. Unlike the standard model that fixes the binary state space {0, 1}, we allow the (binary) unknown state values to be arbitrary numbers in [0, 1], so the same reported probability may correspon...
| Authors | Zhi Chen, Cheng Peng, Wei Tang |
|---|---|
| Primary category | cs.LG |
| Published | 27 April 2026 |
| Last updated at source | 23 May 2026 |
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