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Function-coherent gambles with non-additive sequential dynamics

Conference Paper Artificial Intelligence · Imprecise Probability · Uncertainty in Artificial Intelligence

Abstract

The desirable gambles framework provides a rigorous foundation for imprecise probability theory but relies heavily on linear utility via its coherence axioms. In our related work, we introduced function-coherent gambles to accommodate non-linear utility. However, when repeated gambles are played over time—especially in intertemporal choice where rewards compound multiplicatively—the standard additive combination axiom fails to capture the appropriate long-run evaluation. In this paper we extend the framework by relaxing the additive combination axiom and introducing a nonlinear combination operator that effectively aggregates repeated gambles in the log-domain. This operator preserves the time-average (geometric) growth rate and addresses the ergodicity problem. We prove the key algebraic properties of the operator, discuss its impact on coherence, risk assessment, and representation, and provide a series of illustrative examples. Our approach bridges the gap between expectation values and time averages and unifies normative theory with empirically observed non-stationary reward dynamics.

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Context

Venue
International Symposium on Imprecise Probabilities: Theories and Applications
Archive span
2017-2025
Indexed papers
59
Paper id
386030091338022858
v2026.09.13