As deep neural networks (DNNs) have gained considerable attention in recent years, there have been several cases applying DNNs to portfolio management (PM). Although some researchers have experimentally demonstrated its ability to make a profit, it is still insufficient to use in real situations because existing studies have failed to answer how risky investment decisions are. Furthermore, even though the objective of PM is to maximize returns within a risk tolerance, they overlook the predictive uncertainty of DNNs in the process of risk management. To overcome these limitations, we propose a novel framework called risk-sensitive multiagent network (RSMAN), which includes risk-sensitive agents (RSAs) and a risk adaptive portfolio generator (RAPG). Standard DNNs do not understand the risks of their decision, whereas RSA can take risk-sensitive decisions by estimating market uncertainty and parameter uncertainty. Acting as a trader, this agent is trained via reinforcement learning from dynamic trading simulations to estimate the distribution of reward and via unsupervised learning to assess parameter uncertainty without labeled data. We also present an RAPG that can generate a portfolio fitting the user's risk appetite without retraining by exploiting the estimated information from the RSAs. We tested our framework on the U.S. and Korean real financial markets to demonstrate the practicality of the RSMAN.

Most artificial intelligence (AI) based learning systems act in virtual or laboratory environments. Here we demonstrate an AI-based curling robot system named `Curly' that competes on a real-world curling ice sheet. Curly encompasses (1) an AI-based curling strategy and simulation engine under consideration of the high `icy' uncertainty, (2) the thrower robot enabled by autonomous driving with traction control, and (3) the skip robot that allows to recognize the curling field and stone configuration based on vision technology. The Curly performed well both: in classical game situations and when interacting with human opponents, namely, the top-ranked Korean amateur high school curling team.