Reinforcement Learning Trivia Questions
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Sample Reinforcement Learning Questions
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In this paradigm, an agent improves by receiving positive or negative signals after taking actions in an environment.
- Unsupervised learning
- Supervised learning
- Transfer learning
- Reinforcement learning
This entity interacts with an environment, makes decisions, and learns from the consequences of those decisions.
- Agent
- Model
- Dataset
- Feature
This numerical signal tells an agent whether its action was good or bad, guiding future behavior.
- Loss
- Gradient
- Reward
- Epoch
This represents everything outside the agent that it can interact with and observe in a learning scenario.
- Environment
- Buffer
- Network
- Kernel
This describes all the information available to an agent at a given moment, capturing the current situation.
- Policy
- Episode
- State
- Action
This is a choice the agent makes to influence its environment and change its current situation.
- Reward
- State
- Observation
- Action
This classic game was famously conquered by DeepMind's AI, which learned to play at superhuman level through trial and error.
- Chess
- Minesweeper
- Checkers
- Atari games
This board game saw a historic AI victory in 2016 when DeepMind's system defeated the world champion Lee Sedol.
- Go
- Chess
- Backgammon
- Shogi
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