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Reinforcement Learning

Learning Tactics

Monte Carlo Search

Randomise and find some good samples. Do Monte Carlo for the best value instead of the ratio of number of points in all points.

Explore and Exploit

Explore and exploit is the mainstream strategy in reinforcement learning.

Explore

Consider out there in the wild of unknown cases, there can be better options for action to take. Make a random action.

Explore Rate

Exploration has a rate that reduces in time (the max time, max epochs intended for training) to make the model converge. However, in incremental learning, this explore rate usually never reduces to zero and leave a little bit of exploration.

Exploit

Use the known q-function or q-table, q-network to find the max value with the learnt cases to take action.

Single Agent System

Multi-agent System

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