contents
1 Introduction to deep reinforcement learning
What is deep reinforcement learning?
The past, present, and future of deep reinforcement learning
The suitability of deep reinforcement learning
Setting clear two-way expectations
2 Mathematical foundations of reinforcement learning
Components of reinforcement learning
MDPs: The engine of the environment
3 Balancing immediate and long-term goals
The objective of a decision-making agent
Planning optimal sequences of actions
4 Balancing the gathering and use of information
The challenge of interpreting evaluative feedback
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