1What is the main purpose of image classification?
Computer Vision (Overview of Image Classification, Overview of Object Detection) for Intelligent Systems and Robotics
Easy
A.To assign a label to an image
B.To translate spoken words
C.To measure battery power
D.To control motor speed
Correct Answer: To assign a label to an image
Explanation:
Image classification identifies the main category or label of an image, such as "cat" or "car".
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2What does object detection identify in an image?
Computer Vision (Overview of Image Classification, Overview of Object Detection) for Intelligent Systems and Robotics
Easy
A.Only the file size
B.Only the image color
C.The camera battery level
D.Objects and their locations
Correct Answer: Objects and their locations
Explanation:
Object detection finds objects in an image and usually marks their locations with bounding boxes.
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3Which task is an example of image classification?
Computer Vision (Overview of Image Classification, Overview of Object Detection) for Intelligent Systems and Robotics
Easy
A.Changing a picture into audio
B.Drawing a box around every dog
C.Increasing the robot's wheel speed
D.Deciding whether a picture shows a dog
Correct Answer: Deciding whether a picture shows a dog
Explanation:
Image classification assigns a category to an entire image, such as identifying a dog.
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4What is a bounding box used for in object detection?
Computer Vision (Overview of Image Classification, Overview of Object Detection) for Intelligent Systems and Robotics
Easy
A.To mark an object's location
B.To increase image brightness
C.To record microphone input
D.To store a robot's program
Correct Answer: To mark an object's location
Explanation:
A bounding box is a rectangle drawn around a detected object to show where it appears.
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5What does Natural Language Processing mainly help computers understand?
Natural Language Processing (NLP Fundamentals, Chatbots and Conversational AI) for Intelligent Systems and Robotics
Easy
A.Battery temperature
B.Wheel movement
C.Human language
D.Image brightness
Correct Answer: Human language
Explanation:
Natural Language Processing, or NLP, enables computers to process and understand human language.
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6Which is an example of an NLP application?
Natural Language Processing (NLP Fundamentals, Chatbots and Conversational AI) for Intelligent Systems and Robotics
Easy
A.Speech recognition
B.Motor repair
C.Object gripping
D.Battery charging
Correct Answer: Speech recognition
Explanation:
Speech recognition uses NLP techniques to convert spoken language into text or commands.
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7What is a chatbot?
Natural Language Processing (NLP Fundamentals, Chatbots and Conversational AI) for Intelligent Systems and Robotics
Easy
A.A camera that detects colors
B.A motor that moves a robot
C.A sensor that measures distance
D.A program that communicates with users
Correct Answer: A program that communicates with users
Explanation:
A chatbot is a software system that interacts with people through text or speech.
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8What is the purpose of conversational AI?
Natural Language Processing (NLP Fundamentals, Chatbots and Conversational AI) for Intelligent Systems and Robotics
Easy
A.To support human-like interaction
B.To measure room temperature
C.To reduce camera size
D.To improve wheel traction
Correct Answer: To support human-like interaction
Explanation:
Conversational AI allows systems to understand messages and respond in a natural conversational manner.
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9What is text classification in NLP?
Natural Language Processing (NLP Fundamentals, Chatbots and Conversational AI) for Intelligent Systems and Robotics
Easy
A.Assigning categories to text
B.Measuring sound volume
C.Moving a robot arm
D.Locating objects in images
Correct Answer: Assigning categories to text
Explanation:
Text classification places text into categories, such as positive or negative sentiment.
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10In reinforcement learning, what is an agent?
Reinforcement Learning (Concepts - Agent, State, Action, Reward) in context Intelligent Systems and Robotics
Easy
A.The score received after acting
B.The current situation description
C.The learner or decision-maker
D.The surrounding environment
Correct Answer: The learner or decision-maker
Explanation:
The agent is the system that observes situations, chooses actions, and learns from feedback.
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11What does the state represent in reinforcement learning?
Reinforcement Learning (Concepts - Agent, State, Action, Reward) in context Intelligent Systems and Robotics
Easy
A.The selected movement
B.The learning score
C.The current situation
D.The system designer
Correct Answer: The current situation
Explanation:
A state describes the current condition of the agent and its environment.
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12What is an action in reinforcement learning?
Reinforcement Learning (Concepts - Agent, State, Action, Reward) in context Intelligent Systems and Robotics
Easy
A.A collection of training examples
B.A description of the environment
C.A choice made by the agent
D.A reward value from the system
Correct Answer: A choice made by the agent
Explanation:
An action is a decision or movement selected by the agent, such as turning left.
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13What does a reward provide to an agent?
Reinforcement Learning (Concepts - Agent, State, Action, Reward) in context Intelligent Systems and Robotics
Easy
A.A camera image
B.Feedback about an action
C.A list of possible sensors
D.A fixed movement command
Correct Answer: Feedback about an action
Explanation:
A reward tells the agent how useful or successful an action was.
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14A robot receives a positive reward for reaching a target. What should it learn to do?
Reinforcement Learning (Concepts - Agent, State, Action, Reward) in context Intelligent Systems and Robotics
Easy
A.Ignore the target location
B.Repeat actions that help reach targets
C.Choose actions randomly forever
D.Avoid using its sensors
Correct Answer: Repeat actions that help reach targets
Explanation:
Reinforcement learning encourages an agent to repeat actions that produce positive rewards.
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15What is an autonomous robot?
AI for Autonomous Robots
Easy
A.A robot that only works when unplugged
B.A robot controlled by a fixed photograph
C.A robot that acts with limited human control
D.A robot that has no sensors
Correct Answer: A robot that acts with limited human control
Explanation:
An autonomous robot can sense its surroundings, make decisions, and perform tasks with limited direct control.
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16Which capability helps an autonomous robot avoid obstacles?
AI for Autonomous Robots
Easy
A.Changing the screen font
B.Printing extra instructions
C.Sensing and environment mapping
D.Playing background music
Correct Answer: Sensing and environment mapping
Explanation:
Sensors and mapping help a robot detect obstacles and understand where it can move.
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17Why do autonomous robots use computer vision?
AI for Autonomous Robots
Easy
A.To recharge their batteries
B.To replace all mechanical parts
C.To increase their physical weight
D.To interpret visual surroundings
Correct Answer: To interpret visual surroundings
Explanation:
Computer vision helps robots understand information from cameras, such as objects, paths, and obstacles.
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18Which task can AI help an autonomous robot perform?
AI for Autonomous Robots
Easy
A.Making all sensors unnecessary
B.Changing metal into plastic
C.Removing gravity from the room
D.Planning a route to a destination
Correct Answer: Planning a route to a destination
Explanation:
AI can help robots plan paths and choose actions that move them safely toward a destination.
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19Which is a likely future trend in intelligent robotics?
Future Trends in AI for Intelligent Systems and Robotics
Easy
A.Less use of useful sensors
B.Removal of all safety systems
C.Replacement of software with paper
D.More human-robot collaboration
Correct Answer: More human-robot collaboration
Explanation:
Future robots are expected to work more closely and safely with people in homes, workplaces, and public spaces.
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20What does explainable AI aim to provide?
Future Trends in AI for Intelligent Systems and Robotics
Easy
A.More colorful camera lenses
B.Faster battery charging
C.Understandable reasons for decisions
D.Larger robot wheels
Correct Answer: Understandable reasons for decisions
Explanation:
Explainable AI helps people understand why an AI system produced a particular result.
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21A warehouse robot receives an image containing three boxes and two workers. It must identify each object's category and location. Which computer vision task is most suitable?
Computer Vision (Overview of Image Classification, Overview of Object Detection) for Intelligent Systems and Robotics
Medium
A.Object detection
B.Image classification
C.Color correction
D.Image compression
Correct Answer: Object detection
Explanation:
Object detection identifies multiple objects and predicts a location, usually a bounding box, for each one.
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22An inspection robot classifies product images correctly during training but performs poorly on images captured under different factory lighting. Which change would most directly improve robustness?
Computer Vision (Overview of Image Classification, Overview of Object Detection) for Intelligent Systems and Robotics
Medium
A.Reducing every image to one pixel
B.Applying brightness-based data augmentation
C.Training only on darker images
D.Removing the validation dataset
Correct Answer: Applying brightness-based data augmentation
Explanation:
Brightness-based augmentation exposes the model to varied lighting conditions, helping it generalize to new factory environments.
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23A robot must detect small tools scattered across a workbench. The detector frequently misses tools that occupy very few pixels. Which adjustment is most likely to help?
Computer Vision (Overview of Image Classification, Overview of Object Detection) for Intelligent Systems and Robotics
Medium
Higher-resolution images preserve more visual detail for small objects, making their features easier for a detector to recognize.
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24An object detector predicts a box for a chair. The predicted box overlaps the labeled box, but their overlap is small compared with their combined area. What does this imply about the Intersection over Union (IoU)?
Computer Vision (Overview of Image Classification, Overview of Object Detection) for Intelligent Systems and Robotics
Medium
A.The IoU must exceed one
B.The IoU is close to one
C.The IoU cannot be computed
D.The IoU is close to zero
Correct Answer: The IoU is close to zero
Explanation:
IoU is . A small intersection relative to the union produces a value near zero.
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25A service robot receives the command, "Take the package to the reception desk." Which NLP output is most useful for planning the task?
Natural Language Processing (NLP Fundamentals, Chatbots and Conversational AI) for Intelligent Systems and Robotics
Medium
A.Intent: classify; object: robot; destination: service
The command expresses a delivery intent, with the package as the object and the reception desk as the destination.
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26A robot hears, "Place it beside the blue container," but two recently mentioned objects could be referred to by "it." What should the conversational system do?
Natural Language Processing (NLP Fundamentals, Chatbots and Conversational AI) for Intelligent Systems and Robotics
Medium
A.Select the nearest object automatically
B.Move both objects beside the container
C.Ignore the pronoun and stop listening
D.Ask which object the user means
Correct Answer: Ask which object the user means
Explanation:
A clarification question resolves the ambiguous reference and reduces the risk of the robot performing the wrong physical action.
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27A multilingual guide robot must understand visitor requests in several languages while using one intent classifier. Which approach is most appropriate?
Natural Language Processing (NLP Fundamentals, Chatbots and Conversational AI) for Intelligent Systems and Robotics
Medium
A.Assign a separate intent to each speaker
B.Use multilingual language representations
C.Remove words that differ across languages
D.Translate every request with word substitution
Correct Answer: Use multilingual language representations
Explanation:
Multilingual representations map semantically similar expressions across languages into compatible features for intent classification.
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28A chatbot controlling a home robot correctly identifies the intent "set temperature" but cannot execute "Set it to 22 degrees." Which missing capability is the most likely cause?
Natural Language Processing (NLP Fundamentals, Chatbots and Conversational AI) for Intelligent Systems and Robotics
Medium
A.Object detection for the thermostat
B.Entity extraction for the temperature value
C.Image segmentation for the room layout
D.Reward shaping for motor control
Correct Answer: Entity extraction for the temperature value
Explanation:
The chatbot must extract the value 22 as a temperature entity before it can create the correct control command.
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29A cleaning robot uses reinforcement learning. At a particular moment, its sensor readings indicate its position, battery level, and nearby obstacles. Together, these values represent the robot's:
Reinforcement Learning (Concepts - Agent, State, Action, Reward) in context Intelligent Systems and Robotics
Medium
A.Policy update
B.State
C.Action
D.Reward
Correct Answer: State
Explanation:
The state summarizes information about the current situation that the agent uses to choose an action.
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30A delivery robot earns for completing a delivery, for a collision, and for every minute used. What behavior does this reward design encourage?
Reinforcement Learning (Concepts - Agent, State, Action, Reward) in context Intelligent Systems and Robotics
Medium
A.Fast delivery while avoiding collisions
B.Frequent collisions followed by recovery
C.Slow movement regardless of delivery
D.Remaining stationary to preserve battery
Correct Answer: Fast delivery while avoiding collisions
Explanation:
The completion reward encourages delivery, while collision and time penalties encourage safe and efficient routes.
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31A robotic arm always selects the action with the highest current estimated value and never tries alternatives. What learning problem may result?
Reinforcement Learning (Concepts - Agent, State, Action, Reward) in context Intelligent Systems and Robotics
Medium
A.It may turn rewards into sensor readings
B.It may eliminate all possible actions
C.It may miss a better action
D.It may receive too many state variables
Correct Answer: It may miss a better action
Explanation:
Without exploration, the agent may keep exploiting an action that appears best and never discover a more rewarding alternative.
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32A robot receives a reward of now and a reward of one step later. If the discount factor is , what is the two-step discounted return?
Reinforcement Learning (Concepts - Agent, State, Action, Reward) in context Intelligent Systems and Robotics
Medium
A.
B.
C.
D.
Correct Answer:
Explanation:
The discounted return is .
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33An autonomous mobile robot detects a person unexpectedly entering its planned path. Which response best demonstrates closed-loop autonomy?
AI for Autonomous Robots
Medium
A.Wait for a remote operator every time
B.Continue along the original stored route
C.Delete the map and restart the mission
D.Sense the person, replan, and adjust motion
Correct Answer: Sense the person, replan, and adjust motion
Explanation:
Closed-loop autonomy uses current sensor feedback to update plans and actions as the environment changes.
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34A robot uses wheel odometry for navigation, but its estimated position gradually becomes inaccurate because the wheels sometimes slip. Which additional capability best addresses this problem?
AI for Autonomous Robots
Medium
A.More spoken commands from the user
B.Faster wheel rotation during every turn
C.Sensor fusion with camera or LiDAR data
D.A larger battery for longer operation
Correct Answer: Sensor fusion with camera or LiDAR data
Explanation:
Combining odometry with external observations can correct accumulated position errors caused by wheel slip.
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35A farm robot must navigate through a field it has never seen while building a map and estimating its own location. Which technique is most relevant?
AI for Autonomous Robots
Medium
A.Simultaneous Localization and Mapping
B.Supervised image classification
C.Database transaction processing
D.Natural language generation
Correct Answer: Simultaneous Localization and Mapping
Explanation:
SLAM enables a robot to construct a map of an unknown environment while simultaneously estimating its location within that map.
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36An autonomous drone's navigation model works well in simulation but becomes unstable in real wind. Which training strategy most directly reduces this simulation-to-reality gap?
AI for Autonomous Robots
Medium
A.Randomize wind and dynamics during simulation
B.Use one fixed route for all training
C.Remove motion sensors from the drone
D.Train only in perfectly still simulation
Correct Answer: Randomize wind and dynamics during simulation
Explanation:
Domain randomization exposes the policy to varied simulated conditions, increasing its ability to handle real-world differences.
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37A next-generation household robot combines camera input, spoken instructions, and touch sensor readings to decide how to handle an object. Which emerging trend does this illustrate?
Future Trends in AI for Intelligent Systems and Robotics
Medium
A.Offline data archiving
B.Static rule execution
C.Single-sensor automation
D.Multimodal AI
Correct Answer: Multimodal AI
Explanation:
Multimodal AI integrates information from different forms of input, such as vision, language, and touch.
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38A medical-assistance robot processes camera data on the device instead of sending every frame to a cloud server. What is the main advantage of this edge AI approach?
Future Trends in AI for Intelligent Systems and Robotics
Medium
A.Unlimited storage and computation
B.Lower latency and improved privacy
C.Automatic removal of model bias
D.Perfect accuracy without retraining
Correct Answer: Lower latency and improved privacy
Explanation:
On-device processing can respond quickly and limits the transmission of sensitive visual data to external servers.
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39A collaborative robot learns a new assembly task from a few worker demonstrations and then adapts when the product shape changes. Which future capability is most clearly represented?
Future Trends in AI for Intelligent Systems and Robotics
Medium
A.Few-shot adaptive learning
B.Single-purpose mechanical design
C.Manual database indexing
D.Fixed preprogrammed control
Correct Answer: Few-shot adaptive learning
Explanation:
Few-shot adaptive learning allows robots to acquire and adjust skills using limited examples rather than extensive retraining.
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40Before deploying an AI robot in a public hospital, engineers test whether its decisions differ unfairly across patient groups and record why each action was selected. Which future priority does this address?
Future Trends in AI for Intelligent Systems and Robotics
Medium
A.Responsible and explainable AI
B.Longer wireless communication range
C.Higher mechanical lifting capacity
D.Faster unsupervised data collection
Correct Answer: Responsible and explainable AI
Explanation:
Testing for unfair outcomes and documenting decision factors supports fairness, accountability, and explainability in robotic systems.
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41A warehouse robot must distinguish between visually similar packages while also locating several packages in the same camera frame. Which model output is most appropriate for this requirement?
Computer Vision (Overview of Image Classification, Overview of Object Detection) for Intelligent Systems and Robotics
Hard
A.A single class label for the entire image
B.A class probability for every image pixel
C.A class label and bounding box for each detected package
D.A depth value for every detected package
Correct Answer: A class label and bounding box for each detected package
Explanation:
Object detection identifies multiple instances and provides both their classes and spatial locations. Image classification normally assigns one or more labels to the entire image without localizing each object.
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42An object detector performs well on daytime validation images but fails when a mobile robot enters a dim warehouse. Training and validation images have similar object categories, but their illumination distributions differ substantially. Which intervention most directly addresses the problem?
Computer Vision (Overview of Image Classification, Overview of Object Detection) for Intelligent Systems and Robotics
Hard
A.Replace bounding-box regression with classification
B.Apply illumination-focused data augmentation
C.Increase the detector's confidence threshold
D.Reduce the number of object categories
Correct Answer: Apply illumination-focused data augmentation
Explanation:
The failure is consistent with a domain shift caused by illumination. Training with brightness, contrast, exposure, and noise variations can improve robustness to the warehouse conditions.
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43A safety-critical robot uses an object detector to identify humans. Missing a person is substantially more dangerous than producing an occasional false alarm. Which evaluation strategy is most appropriate?
Computer Vision (Overview of Image Classification, Overview of Object Detection) for Intelligent Systems and Robotics
Hard
A.Report only the detector's training loss
B.Select the threshold that maximizes precision
C.Select the threshold that prioritizes high recall
D.Optimize only for overall classification accuracy
Correct Answer: Select the threshold that prioritizes high recall
Explanation:
Recall measures the fraction of actual objects that are detected. When false negatives are especially costly, the operating threshold should favor recall, while monitoring the resulting false-positive rate.
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44Two predicted bounding boxes overlap the same ground-truth object with intersection-over-union values of and . A detector uses non-maximum suppression with an IoU threshold of . What normally happens?
Computer Vision (Overview of Image Classification, Overview of Object Detection) for Intelligent Systems and Robotics
Hard
A.The higher-confidence box is suppressed by the lower-confidence box
B.The lower-confidence box is suppressed by the higher-confidence box
C.Both boxes are discarded because their IoU is too large
D.Both boxes are retained because both exceed
Correct Answer: The lower-confidence box is suppressed by the higher-confidence box
Explanation:
Non-maximum suppression retains the highest-confidence box and removes nearby boxes whose overlap with it exceeds the threshold. The overlap triggers suppression of the lower-confidence prediction.
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45A robot's classifier achieves accuracy on a dataset where only of images contain a dangerous obstacle. It correctly detects of dangerous images but incorrectly flags of safe images. Approximately what is the precision of the danger detector?
Computer Vision (Overview of Image Classification, Overview of Object Detection) for Intelligent Systems and Robotics
Hard
A.
B.
C.
D.
Correct Answer:
Explanation:
For images, there are true positives and false positives. Thus, precision is , despite the high overall accuracy.
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46A service robot receives the utterance, "It is cold here; could you close that?" The word "that" refers to a nearby window identified by the robot's vision system. Which NLP capability is most essential for correct interpretation?
Natural Language Processing (NLP Fundamentals, Chatbots and Conversational AI) for Intelligent Systems and Robotics
Hard
A.Character-level spelling correction
B.Part-of-speech tagging without dialogue history
C.Token frequency estimation
D.Coreference resolution using multimodal context
Correct Answer: Coreference resolution using multimodal context
Explanation:
The robot must resolve the referring expression "that" using linguistic context and visual information about nearby objects. This is a multimodal coreference and grounding problem.
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47A chatbot receives the phrase "I need to cancel my appointment tomorrow," but the user has two appointments scheduled for tomorrow. What is the safest conversational response?
Natural Language Processing (NLP Fundamentals, Chatbots and Conversational AI) for Intelligent Systems and Robotics
Hard
A.Reject the request because cancellation is ambiguous
B.Ask the user to identify which appointment
C.Cancel both appointments automatically
D.Cancel the appointment with the earliest time
Correct Answer: Ask the user to identify which appointment
Explanation:
The intent is clear but the required entity is ambiguous. A robust dialogue system should ask a targeted clarification question before taking an irreversible action.
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48A robot assistant is deployed in a hospital. Its language model is highly fluent but sometimes invents medication instructions when retrieval fails. Which design change most directly reduces this safety risk?
Natural Language Processing (NLP Fundamentals, Chatbots and Conversational AI) for Intelligent Systems and Robotics
Hard
A.Ground responses in verified sources with refusal rules
B.Permit unrestricted responses for conversational smoothness
C.Remove uncertainty signals from the user interface
D.Increase the model's temperature during generation
Correct Answer: Ground responses in verified sources with refusal rules
Explanation:
Retrieval grounding constrains medical responses to trusted information, while refusal or escalation rules handle unsupported requests. Fluency alone does not guarantee factual reliability.
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49A multilingual robot receives commands in languages not represented during training. Which approach is most likely to improve intent recognition while preserving a shared downstream policy?
Natural Language Processing (NLP Fundamentals, Chatbots and Conversational AI) for Intelligent Systems and Robotics
Hard
A.Translate all commands into a shared canonical representation
B.Ignore syntax and classify using sentence length
C.Train an independent policy for every language
D.Use language-specific labels with incompatible meanings
Correct Answer: Translate all commands into a shared canonical representation
Explanation:
Mapping different languages to a shared intent and entity representation allows the same downstream action policy to operate across languages, provided translation preserves relevant meaning.
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50A voice-controlled robot must distinguish between "pick up the red cup" and "do not pick up the red cup." Which failure would be especially dangerous if the NLP pipeline relies mainly on keyword matching?
Natural Language Processing (NLP Fundamentals, Chatbots and Conversational AI) for Intelligent Systems and Robotics
Hard
A.Using a shorter synonym for "cup"
B.Failure to recognize a plural noun
C.Ignoring negation scope in the command
D.Confusing two equivalent pronunciations
Correct Answer: Ignoring negation scope in the command
Explanation:
Keyword matching may detect "pick up" and "red cup" while missing that "do not" reverses the action. Correct interpretation requires syntactic and semantic handling of negation.
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51A robot navigates using a camera that cannot observe obstacles behind walls. If the controller treats the current image as the complete state, which assumption is most likely violated?
Reinforcement Learning (Concepts - Agent, State, Action, Reward) in context Intelligent Systems and Robotics
Hard
A.The environment has a finite action set
B.The policy maps inputs to actions
C.The reward is represented by a scalar
D.The observation satisfies the Markov property
Correct Answer: The observation satisfies the Markov property
Explanation:
A state is Markov when it contains enough information to predict future transitions and rewards. A single partial image may omit hidden obstacles, making the problem partially observable.
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52A delivery robot receives a large positive reward when it reaches its destination but no intermediate rewards. Training is slow because successful trajectories are rare. Which modification most directly addresses this issue without changing the final objective?
Reinforcement Learning (Concepts - Agent, State, Action, Reward) in context Intelligent Systems and Robotics
Hard
A.Remove the terminal reward from successful episodes
B.Use reward shaping based on progress toward the destination
C.Increase the discount factor to exactly zero
D.Randomize the action meanings during each episode
Correct Answer: Use reward shaping based on progress toward the destination
Explanation:
Progress-based shaping supplies denser learning signals while retaining the destination objective. The shaping must be designed carefully so that it does not encourage unsafe shortcuts or alter the intended task.
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53A robot receives reward for reaching a target and for every time step. It can choose a risky shortcut or a safe longer route. What behavior does the reward function explicitly encourage?
Reinforcement Learning (Concepts - Agent, State, Action, Reward) in context Intelligent Systems and Robotics
Hard
A.Reaching the target quickly while avoiding excessive steps
B.Maximizing travel time regardless of safety
C.Ignoring the target after receiving the first negative reward
D.Choosing the route with the greatest number of actions
Correct Answer: Reaching the target quickly while avoiding excessive steps
Explanation:
The terminal reward encourages successful completion, while the per-step penalty favors shorter trajectories. Safety is not guaranteed unless collisions or risk are also represented in the reward or constraints.
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54During training, a robot learns to repeatedly approach a charging station and reset because the reset transition accidentally provides a large reward. What is the primary problem?
Reinforcement Learning (Concepts - Agent, State, Action, Reward) in context Intelligent Systems and Robotics
Hard
A.The reward function creates an exploitable loophole
B.The state representation contains too many sensor values
C.The action space is necessarily too continuous
D.The discount factor prevents all repeated behavior
Correct Answer: The reward function creates an exploitable loophole
Explanation:
The agent is optimizing the specified reward rather than the intended task. The reset reward creates a reward-hacking opportunity, so the transition and reward design must be corrected.
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55A robot's policy performs well in simulation but collides with furniture on a real floor because the simulated wheel friction and sensor noise were too idealized. Which strategy most directly improves transfer?
Reinforcement Learning (Concepts - Agent, State, Action, Reward) in context Intelligent Systems and Robotics
Hard
A.Use domain randomization during simulation training
B.Remove sensor inputs from the policy
C.Increase the robot's maximum speed
D.Train only on the single nominal simulator
Correct Answer: Use domain randomization during simulation training
Explanation:
Domain randomization varies friction, dynamics, sensing, lighting, and other conditions during training. Policies exposed to a wider simulated distribution are more likely to generalize to real-world variation.
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56An autonomous delivery robot detects a pedestrian using vision, estimates the pedestrian's motion, plans a path, and sends velocity commands. Which architectural property is most important for safe operation under changing conditions?
AI for Autonomous Robots
Hard
A.A planner that ignores new sensor measurements during execution
B.A single irreversible decision made before deployment
C.A controller that optimizes appearance rather than collision risk
D.A closed-loop cycle of perception, prediction, planning, and control
Correct Answer: A closed-loop cycle of perception, prediction, planning, and control
Explanation:
Autonomous robots operate in dynamic environments, so they must repeatedly update beliefs and actions using new observations. Closed-loop control enables correction when people or obstacles move unexpectedly.
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57A robot has an accurate global map but its localization estimate drifts when wheel slip occurs. Which sensor-fusion improvement is most appropriate?
AI for Autonomous Robots
Hard
A.Use wheel encoders as the only localization source
B.Combine odometry with independent absolute measurements
C.Discard all observations after initialization
D.Increase motor speed to reduce localization uncertainty
Correct Answer: Combine odometry with independent absolute measurements
Explanation:
Wheel odometry accumulates drift, especially under slip. Fusing it with camera, lidar, GPS, landmarks, or other absolute or map-relative measurements can correct the accumulated error.
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58A robot must operate near humans, but its perception model is uncertain because of rain and glare. Which decision policy is most appropriate for a safety-critical action?
AI for Autonomous Robots
Hard
A.Ignore uncertainty because planning occurs afterward
B.Execute the action whenever the top class exceeds
C.Treat model confidence as a guaranteed probability
D.Use uncertainty-aware thresholds and a safe fallback
Correct Answer: Use uncertainty-aware thresholds and a safe fallback
Explanation:
Uncertainty should influence whether the robot proceeds, slows, requests assistance, or stops safely. A confidence score is not automatically a calibrated probability or a guarantee of correctness.
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59A future household robot is expected to perform novel tasks described in natural language and adapt to unfamiliar homes. Which combination of capabilities most directly supports this goal?
Future Trends in AI for Intelligent Systems and Robotics
Hard
A.Higher motor speed, smaller batteries, and static lookup tables
B.Image classification alone with manually scripted trajectories
C.Fixed rules, closed-world assumptions, and no online feedback
D.Foundation models, multimodal grounding, and continual adaptation
Correct Answer: Foundation models, multimodal grounding, and continual adaptation
Explanation:
General-purpose robots need broad pretrained representations, links between language and physical entities, and mechanisms for adapting to new environments and tasks.
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60A robot manufacturer wants to deploy an AI model on an embedded device with limited power and strict response-time requirements. Which trend most directly addresses this constraint?
Future Trends in AI for Intelligent Systems and Robotics
Hard
A.Cloud-only inference with larger network delays
B.Offline operation without any learned perception model
C.Uncompressed models with increased parameter counts
D.Edge AI using model compression and efficient architectures
Correct Answer: Edge AI using model compression and efficient architectures
Explanation:
Quantization, pruning, distillation, and efficient architectures reduce computation and memory requirements, allowing inference to occur locally with lower latency and improved connectivity resilience.
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