ReAct Agent Pattern Quiz

Answers and explanations appear as you take the quiz.

1. What two capabilities does the ReAct pattern combine?
   • Reasoning (thinking) and acting (using tools)
   • Image generation and audio synthesis
   • Encryption and compression
   • Printing and scanning
2. What are the three repeating elements of a ReAct loop?
   • Input, Output, Restart
   • Thought, Action, Observation
   • Encode, Decode, Display
   • Login, Logout, Refresh
3. What is an 'Observation' in the ReAct loop?
   • The model's internal plan
   • A user's password
   • The result returned after taking an action, like a search result
   • A final summary email
4. Why can ReAct reduce hallucination compared with pure chain-of-thought reasoning?
   • It never lets the model reason at all
   • It deletes the model's training data
   • It only works offline
   • It grounds reasoning in real observations from tools and external data
5. What improvement did the ReAct paper report over imitation/RL baselines on ALFWorld?
   • An absolute success-rate improvement of 34 percentage points in its evaluated setup
   • A 100% success rate across all tasks
   • A 34% reduction in tool calls on every benchmark
   • No measurable change
6. Which external source did the ReAct paper use to retrieve observations in its knowledge-intensive QA experiments?
   • A private medical database
   • A Wikipedia API
   • A spreadsheet stored in the model weights
   • An offline dictionary only
7. How can an observation change the next step in a ReAct trajectory?
   • It is always ignored after an action
   • It guarantees the next action is correct
   • The model can revise its plan based on the tool or environment result
   • It automatically becomes the final answer
8. Which task types did the original ReAct paper evaluate?
   • Only image compression
   • Only speech recognition
   • Only spreadsheet formatting
   • Knowledge-intensive question answering and interactive decision-making