In this paper we propose a financial trading system whose strategy is developed by means of an artificial neural network approach based on a recurrent reinforcement learning algo...
We present the first large-scale empirical application of reinforcement learning to the important problem of optimized trade execution in modern financial markets. Our experiments...
As massively multi-player gaming environments become more detailed, developing agents to populate these virtual worlds as capable non-player characters poses an increasingly compl...
John Reeder, Gita Sukthankar, Michael Georgiopoulo...
This paper introduces algorithms for learning how to trade using insider (superior) information in Kyle's model of financial markets. Prior results in finance theory relied o...
We believe that communication in multi-agent system has two major meanings. One of them is to transmit one agent's observed information to the other. The other meaning is to ...