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2 changes: 1 addition & 1 deletion 01-introduction-to-decision-making/README.md
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Expand Up @@ -35,7 +35,7 @@ difference between Reinforcement Learning and other related fields. Reinforcemen
relaxes this constraint allowing the notion of sequential decision-making.
This sense of interaction with an environment sets Reinforcement Learning apart. In later lessons,
we will continue losing constraints and presenting more abstract topics related to Reinforcement
Learning. After this lesson, we will explore deterministic and stochastic transitions, know
Learning. After this lesson, we will explore deterministic and stochastic transitions, known
and unknown environments, discrete and continuous states, discrete and continuous actions,
observable and partially observable states, single and multiple agents, cooperative and
adversarial agents, and finally, we will put everything in the perspective of human
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