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Found 6 papers, 1 papers with code
Finding Near-Optimal Portfolios With Quality-Diversity
In this paper, we present a novel approach for finding a diverse set of such portfolios based on quality-diversity (QD) optimization.
A New Angle: On Evolving Rotation Symmetric Boolean Functions
Rotation symmetric Boolean functions represent an interesting class of Boolean functions as they are relatively rare compared to general Boolean functions.
Deep Reinforcement Learning for Robust Goal-Based Wealth Management
Goal-based investing is an approach to wealth management that prioritizes achieving specific financial goals.
On Evolvability and Behavior Landscapes in Neuroevolutionary Divergent Search
Finally, a novel definition of evolvability that takes into account the evolvability of offspring and is appropriate for use with discretized behavior spaces is proposed, together with a Markov-chain-based estimation method for it.
A Search for Nonlinear Balanced Boolean Functions by Leveraging Phenotypic Properties
In the context of the underlying problem, the phenotypes are represented by Walsh-Hadamard spectra of the candidate solutions (Boolean functions).
Deep Reinforcement Learning for Market Making Under a Hawkes Process-Based Limit Order Book Model
The stochastic control problem of optimal market making is among the central problems in quantitative finance.
