Counterfactual Regret Evolutionary Agents (CREA): A Mathematical Framework for Adaptive Decision-Making in Financial Systems under Deep Uncertainty
A rigorous mathematical framework for adaptive decision-making under deep uncertainty. CREA integrates probability spaces, stochastic price dynamics, structural causal discovery (NOTEARS, DAG-GNN, PCMCI), fuzzy ambiguity modeling, CVaR-based tail-risk control, Wasserstein distributionally robust optimization, transformer memory architectures, and meta-evolutionary optimization to discover strategies that remain stable across multiple counterfactual market futures.