Handling conflicts between agents in Agentic AI - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to initialize the conflict resolution method for agents.

Agentic AI

conflict_resolver = AgentConflictManager([1]=True)

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

Aenable_resolution

Ballow_conflicts

Cconflict_mode

Dresolve_conflicts

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'allow_conflicts' which would permit conflicts instead of resolving them.

Using 'conflict_mode' which is not a valid parameter.

The parameter 'resolve_conflicts' enables the conflict resolution mechanism between agents.

2fill in blank

medium

Complete the code to detect conflicts between two agents' actions.

Agentic AI

if agent1.action [1] agent2.action:
    handle_conflict()

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

A!=

B==

Cin

Dnot in

Attempts:

3 left

💡 Hint

Common Mistakes

Using '==' which checks if actions are the same, not conflicting.

Using 'in' or 'not in' which are not appropriate for direct action comparison.

Conflicts occur when the actions are different, so '!=' is used to detect conflicting actions.

3fill in blank

hard

Fix the error in the conflict resolution function call.

Agentic AI

result = resolve_conflict(agent1, agent2, strategy=[1])

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

A'priority'

Brandom

C'random'

Dpriority

Attempts:

3 left

💡 Hint

Common Mistakes

Passing the strategy without quotes causing a NameError.

Using an undefined variable instead of a string literal.

The strategy parameter expects a string, so the value must be in quotes.

4fill in blank

hard

Fill both blanks to create a dictionary mapping agents to their chosen conflict resolution strategies.

Agentic AI

strategies = {agent1: [1], agent2: [2]

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

A'compromise'

B'voting'

C'negotiation'

D'arbitration'

Attempts:

3 left

💡 Hint

Common Mistakes

Using non-string values without quotes.

Assigning the same strategy to both agents.

Assigning 'compromise' to agent1 and 'negotiation' to agent2 shows different conflict resolution strategies.

5fill in blank

hard

Fill all three blanks to filter conflicting agents and apply a resolution method.

Agentic AI

conflicting_agents = [agent for agent in agents if agent.status == [1]]
resolution_method = [2]
results = [resolution_method(agent) for agent in conflicting_agents if agent.priority [3] 5]

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

A'conflicted'

Bresolve_agent_conflict

C>

D<

Attempts:

3 left

💡 Hint

Common Mistakes

Using wrong status string without quotes.

Using a comparison operator that selects lower priority agents.

Passing a string instead of a function for the resolution method.

We filter agents with status 'conflicted', use the function 'resolve_agent_conflict', and apply it only to agents with priority greater than 5.

Practice

1. What is the main purpose of handling conflicts between agents in a multi-agent system?

easy

A. To help agents agree and cooperate effectively

B. To make agents work independently without interaction

C. To increase the number of conflicts between agents

D. To stop agents from making any decisions

Solution

1. Step 1: Understand agent interaction

   Agents in a system often need to work together, which can cause conflicts.

2. Step 2: Purpose of conflict handling

   Handling conflicts helps agents reach agreement and cooperate smoothly.

3. Final Answer:

   To help agents agree and cooperate effectively -> Option A

4. Quick Check:

   Conflict handling = cooperation [OK]

Hint: Conflict handling means making agents cooperate, not compete [OK]

Common Mistakes:

• Thinking conflicts should be increased
• Believing agents should work without interaction
• Assuming agents should stop deciding

2. Which of the following is a correct simple method to resolve conflicts between agents?

easy

A. Making agents decide randomly without rules

B. Ignoring all agent decisions

C. Stopping agents from communicating

D. Prioritizing one agent's decision over others

Solution

1. Step 1: Review conflict resolution methods

   Common simple methods include prioritizing, voting, or random choice.

2. Step 2: Identify correct method

   Prioritizing one agent's decision is a valid and simple conflict resolution method.

3. Final Answer:

   Prioritizing one agent's decision over others -> Option D

4. Quick Check:

   Simple conflict method = prioritizing [OK]

Hint: Prioritize decisions to resolve conflicts simply [OK]

Common Mistakes:

• Ignoring decisions removes cooperation
• Random decisions without rules cause chaos
• Stopping communication prevents resolution

3. Consider two agents voting on a decision: Agent A votes 'Yes', Agent B votes 'No', Agent C votes 'Yes'. If the system resolves conflicts by majority voting, what is the final decision?

medium

A. No

B. Yes

C. Tie

D. Random choice

Solution

1. Step 1: Count votes from agents

   Agent A: Yes, Agent B: No, Agent C: Yes. Yes votes = 2, No votes = 1.

2. Step 2: Apply majority voting rule

   The majority is 'Yes' with 2 votes, so the final decision is 'Yes'.

3. Final Answer:

   Yes -> Option B

4. Quick Check:

   Majority votes = Yes [OK]

Hint: Count votes; majority wins [OK]

Common Mistakes:

• Counting tie when there is none
• Choosing random instead of majority
• Ignoring one agent's vote

4. The following code snippet is intended to resolve conflicts by selecting the agent with the highest priority. What is the error?

agents = [{'name': 'A', 'priority': 2}, {'name': 'B', 'priority': 5}, {'name': 'C', 'priority': 3}]
selected = max(agents, key=lambda x: x['priority'])
print(selected['name'])

medium

A. The code correctly selects the agent with highest priority

B. The lambda function syntax is wrong

C. The max function is used incorrectly

D. The agents list should be sorted before max

Solution

1. Step 1: Analyze max function usage

   The max function with key=lambda x: x['priority'] correctly finds the agent with highest priority.

2. Step 2: Check lambda syntax and list usage

   The lambda syntax is correct, and the list is properly structured.

3. Final Answer:

   The code correctly selects the agent with highest priority -> Option A

4. Quick Check:

   max with key = correct usage [OK]

Hint: max with key finds highest priority correctly [OK]

Common Mistakes:

• Thinking max needs sorted list
• Misreading lambda syntax
• Assuming max is incorrect without reason

5. In a system where three agents must agree on a decision, Agent X has priority 3, Agent Y priority 2, and Agent Z priority 1. If Agent X and Agent Z disagree but Agent Y agrees with Agent Z, which conflict resolution method best ensures a fair decision?

hard

A. Randomly pick between Agent X and Z

B. Always choose Agent X's decision

C. Use weighted voting based on priority

D. Ignore Agent Y's vote

Solution

1. Step 1: Understand agent priorities and votes

   Agent X (priority 3) disagrees with Agent Z (priority 1), Agent Y (priority 2) agrees with Z.

2. Step 2: Evaluate conflict resolution methods

   Weighted voting uses priorities to weigh votes fairly, reflecting influence of each agent.

3. Step 3: Choose best method for fairness

   Weighted voting balances influence and agreement, better than always choosing one agent or random choice.

4. Final Answer:

   Use weighted voting based on priority -> Option C

5. Quick Check:

   Weighted voting = fair conflict resolution [OK]

Hint: Weight votes by priority for fair decisions [OK]

Common Mistakes:

• Always trusting highest priority agent
• Ignoring votes of middle priority agent
• Choosing randomly without weights