Research assistant agent in Agentic Ai - Practice Problems & Coding Challenges

Challenge - 5 Problems

🧠 conceptual

intermediate

How does a research assistant agent prioritize tasks?

A research assistant agent receives multiple tasks such as summarizing papers, extracting data, and generating reports. How does it decide which task to do first?

A It always does the easiest task first to finish quickly.

B It randomly picks any task without considering importance or deadlines.

C It waits for a human to assign the next task each time.

D It prioritizes tasks based on deadlines and relevance to the main research goal.

💻 code output

intermediate

Output of a simple research assistant agent task queue

What will be the output of the following Python code simulating a research assistant agent's task queue?

Agentic_ai

tasks = ['summarize paper', 'extract data', 'generate report']
completed = []

while tasks:
    task = tasks.pop(0)
    completed.append(f"Done: {task}")

print(completed)

A ['Done: summarize paper', 'Done: extract data', 'Done: generate report']

B ['Done: generate report', 'Done: extract data', 'Done: summarize paper']

C ['summarize paper', 'extract data', 'generate report']

D []

❓ model choice

advanced

Best model type for a research assistant agent summarizing papers

Which model type is most suitable for a research assistant agent tasked with summarizing scientific papers?

A A convolutional neural network (CNN) designed for image recognition.

B A recurrent neural network (RNN) or transformer model trained on text summarization.

C A clustering algorithm like K-means for grouping data points.

D A reinforcement learning model for playing games.

❓ hyperparameter

advanced

Choosing hyperparameters for a research assistant agent's text summarization model

Which hyperparameter adjustment is most likely to improve the quality of summaries generated by a transformer-based research assistant agent?

A Increasing the learning rate drastically to speed up training.

B Reducing the number of attention heads to simplify the model.

C Increasing the maximum sequence length to capture more context.

D Decreasing the batch size to zero.

❓ metrics

expert

Evaluating a research assistant agent's summarization quality

A research assistant agent generates summaries of research papers. Which metric best measures how well the summaries capture the original content?

A BLEU score comparing generated summary to reference summary.

B Mean squared error between summary and original text embeddings.

C Accuracy of classification labels.

D Confusion matrix of predicted vs actual categories.