Tag: Monte

The Monte Carlo (MC) and the Temporal-Difference (TD) methods are both fundamental technics in the field of reinforcement learning; they solve the prediction problem based on the experiences from interacting with the environment rather than the environment’s model. However, the TD method is a ...

In Reinforcement Learning, we either use Monte Carlo (MC) estimates or Temporal Difference (TD) learning to establish the ‘target’ return from sample episodes. Both approaches allow us to learn from an environment in which transition dynamics are unknown, i.e., p(s',r|s,a) ...

When the Simulation method is called, we use the GameState of the given MCTS_Node to create a hypothetical round of the card game. We simulate each phase in order, before finally simulating the switching of the turn. The Play Phase is the meat of the turn, ...

On October 14th, La Monte Young played at the Dream House, 275 Church Street, in the building where he and his wife and collaborator Marian Zazeela live. It was his 82nd birthday. By 9pm a small crowd had gathered in the street outside, under scaffolding outside bars and pizza restaurants. Asi...

The modern variant of the “Monte Carlo Methods” can be traced back to the Los Alamos Laboratory in the 1940s, where it was originally developed to assist with modeling the nuclear fission process, in particular, simulating the mean free path of neutrons in fissile materials. Rather than ...

Step into the realm where chance meets calculation, where randomness is harnessed to unlock the secrets of complex systems. Welcome to the world of Monte Carlo simulation, a realm where probabilities reign supreme and predictions come to life with each roll of the digital dice. Join us on a journey ...

In the field of probability and statistics, it is not uncommon to encounter situations where the probability distribution function cannot be calculated directly. One example of such a situation is the Bayesian inference. A popular example of Bayesian inference is the estimation of model parameter...

Forecasting financial markets is a sophisticated fusion of quantitative precision and global economic nuance. In this quest, the Monte Carlo simulation stands out as a premier statistical instrument, guiding our understanding of future stock prices. Named after the famous Monte Carlo Casino in Mo...