When to use which reasoning pattern in Agentic AI - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to select the reasoning pattern for simple yes/no questions.

Agentic AI

def choose_reasoning_pattern(question):
    if question.lower().startswith('is') or question.lower().startswith('are'):
        return '[1]'
    else:
        return 'complex reasoning'

Drag options to blanks, or click blank then click option'

Abinary reasoning

Bcausal reasoning

Canalogical reasoning

Dabductive reasoning

Attempts:

3 left

💡 Hint

Common Mistakes

Choosing a reasoning pattern meant for complex cause-effect relations.

Binary reasoning is best for simple yes/no questions.

2fill in blank

medium

Complete the code to select causal reasoning for cause-effect questions.

Agentic AI

def choose_reasoning_pattern(question):
    if 'because' in question or 'why' in question:
        return '[1]'
    else:
        return 'other reasoning'

Drag options to blanks, or click blank then click option'

Adeductive reasoning

Bbinary reasoning

Canalogical reasoning

Dcausal reasoning

Attempts:

3 left

💡 Hint

Common Mistakes

Using binary reasoning for cause-effect questions.

Causal reasoning is used to understand cause and effect, often triggered by 'why' or 'because'.

3fill in blank

hard

Fix the error in the code to correctly select analogical reasoning for similarity questions.

Agentic AI

def choose_reasoning_pattern(question):
    if 'like' in question or 'similar to' in question:
        return '[1]'
    else:
        return 'other reasoning'

Drag options to blanks, or click blank then click option'

Abinary reasoning

Bcausal reasoning

Canalogical reasoning

Dinductive reasoning

Attempts:

3 left

💡 Hint

Common Mistakes

Confusing causal reasoning with analogical reasoning.

Analogical reasoning compares similarities, triggered by words like 'like' or 'similar to'.

4fill in blank

hard

Fill both blanks to select abductive reasoning for best explanation questions.

Agentic AI

def choose_reasoning_pattern(question):
    if question.lower().startswith('[1]') or 'best explanation' in question:
        return '[2]'
    else:
        return 'other reasoning'

Drag options to blanks, or click blank then click option'

Awhat if

Babductive reasoning

Cwhy

Dbinary reasoning

Attempts:

3 left

💡 Hint

Common Mistakes

Using binary reasoning for explanation questions.

Abductive reasoning is used to find the best explanation, often triggered by 'why' questions.

5fill in blank

hard

Fill all three blanks to select deductive reasoning for rule-based questions.

Agentic AI

def choose_reasoning_pattern(question):
    if '[1]' in question or question.lower().startswith('[2]'):
        return '[3]'
    else:
        return 'other reasoning'

Drag options to blanks, or click blank then click option'

Aif

Bdoes

Cdeductive reasoning

Dwhy

Attempts:

3 left

💡 Hint

Common Mistakes

Using abductive reasoning for rule-based questions.

Deductive reasoning applies rules and logic, often triggered by 'if' or 'does' in questions.

Practice

1. Which reasoning pattern is best when you want a clear, step-by-step explanation from an AI?

easy

A. Step-by-step reasoning

B. Direct reasoning

C. Probabilistic reasoning

D. Hybrid reasoning

Solution

1. Step 1: Understand the purpose of step-by-step reasoning

   Step-by-step reasoning breaks down problems into clear, ordered steps for easy understanding.

2. Step 2: Match the pattern to the task

   When you want clear explanations, step-by-step is the best fit because it shows each part of the process.

3. Final Answer:

   Step-by-step reasoning -> Option A

4. Quick Check:

   Clear explanation = Step-by-step reasoning [OK]

Hint: Choose step-by-step for clear, detailed explanations [OK]

Common Mistakes:

• Confusing direct reasoning with step-by-step
• Using probabilistic reasoning for simple tasks
• Thinking hybrid reasoning is always best

2. Which of the following is the correct syntax to describe direct reasoning in AI?

easy

A. AI solves problem by breaking into steps

B. AI guesses answer based on chance

C. AI gives answer immediately without steps

D. AI mixes step-by-step and guessing

Solution

1. Step 1: Understand direct reasoning meaning

   Direct reasoning means AI gives an answer immediately without showing steps.

2. Step 2: Match syntax to meaning

   AI gives answer immediately without steps correctly describes direct reasoning as giving an answer immediately without steps.

3. Final Answer:

   AI gives answer immediately without steps -> Option C

4. Quick Check:

   Direct reasoning = immediate answer [OK]

Hint: Direct reasoning means no steps, just answer [OK]

Common Mistakes:

• Mixing step-by-step with direct reasoning
• Thinking direct reasoning involves guessing
• Confusing hybrid reasoning with direct

3. Given this code snippet simulating reasoning patterns, what will be the output?

def reasoning(pattern):
    if pattern == 'direct':
        return 'Answer immediately'
    elif pattern == 'step':
        return 'Explain step 1, then step 2'
    elif pattern == 'probabilistic':
        return 'Guess with chance'
    else:
        return 'Unknown pattern'

print(reasoning('step'))

medium

A. Answer immediately

B. Explain step 1, then step 2

C. Guess with chance

D. Unknown pattern

Solution

1. Step 1: Check the input to the function

   The function is called with 'step' as the pattern argument.

2. Step 2: Follow the if-elif conditions

   When pattern is 'step', the function returns 'Explain step 1, then step 2'.

3. Final Answer:

   Explain step 1, then step 2 -> Option B

4. Quick Check:

   Input 'step' returns explanation steps [OK]

Hint: Match input string to if-elif return value [OK]

Common Mistakes:

• Choosing output for 'direct' instead of 'step'
• Ignoring else case
• Misreading the function logic

4. This code is meant to select a reasoning pattern based on problem complexity. What is the bug?

def select_pattern(complexity):
    if complexity > 5:
        return 'step-by-step'
    elif complexity > 10:
        return 'probabilistic'
    else:
        return 'direct'

print(select_pattern(12))

medium

A. Print statement syntax is incorrect

B. Missing return statement in else block

C. Function does not handle complexity less than 0

D. The order of conditions is wrong; higher complexity checked second

Solution

1. Step 1: Analyze the if-elif conditions order

   The first condition checks if complexity > 5, which is true for 12, so it returns immediately.

2. Step 2: Identify the logic error

   The second condition (complexity > 10) is never reached because the first condition is broader and comes first.

3. Final Answer:

   The order of conditions is wrong; higher complexity checked second -> Option D

4. Quick Check:

   Check condition order for correct logic [OK]

Hint: Check if conditions from most specific to general [OK]

Common Mistakes:

• Ignoring condition order importance
• Assuming else block missing return causes error
• Thinking print syntax is wrong

5. You have a complex problem with uncertain data and need the AI to both guess and explain some steps. Which reasoning pattern should you choose?

hard

A. Hybrid reasoning

B. Step-by-step reasoning

C. Direct reasoning

D. Probabilistic reasoning

Solution

1. Step 1: Understand problem needs

   The problem is complex with uncertain data and requires both guessing and explanation.

2. Step 2: Match reasoning pattern to needs

   Hybrid reasoning combines step-by-step explanation and probabilistic guessing, fitting the problem best.

3. Final Answer:

   Hybrid reasoning -> Option A

4. Quick Check:

   Complex + uncertain + explanation = Hybrid reasoning [OK]

Hint: Use hybrid for complex, uncertain, and explanatory tasks [OK]

Common Mistakes:

• Choosing only probabilistic reasoning for explanation
• Picking direct reasoning for complex problems
• Ignoring hybrid as a combined approach