Neuro-symbolic Meta Reinforcement Learning for Trading

Further, we observe a meta-pattern games, strategy games, robotics, etc. In many of these arenas, in such hand-crafted patterns which we use to automatically the spectrum of human performance varies widely, from learn a large number of similar features using techniques average to expert. Human traders in financial markets also borrowed from inductive logic programming, and investigate differ greatly in skill and performance. The consistent success whether these add to the effectiveness of our meta-RL of expert traders is unlikely to be due to chance alone; based trading agent. We present preliminary results on real it is more likely that such traders are explicitly or implicitly data that indicate that both meta reinforcement learning and relying on patterns in the data they see.