Ai Viva Questions
ARTIFICIAL INTELLIGENCE
VIVA QUESTIONS
1. Definitions
Agent
Constraint Satisfaction
Expert system
Game playing
Genetic Algorithm and genetic programming
Knowledge acquisition
Knowledge representation
Logic programming prolog
Machine learning
Natural language processing
Robotics
Simulated annealing
Uncertainty
Vision
Search and game playing
Logic
Planning
Probabilistic reasoning
Nonmonotonic Reasoning and truth maintenance systems (TMS)
2. A*: A search algorithm to find the shortest path through a search space to a goal state using a heuristic. See ‘search’, ‘problem space’, admissibility’ and ‘heuristic’.
3. Admissibility:
An admissible search algorithm is one that is guaranteed to find the optimal path fron the start node to a goal node, if one exists. In A* search, an admissible heuristic is one that never overestimated the distance remaining from the current node to the goal.
4. Agent
“Anything that can be viewed a perceiving its environment through sensors and acting upon that environment through effectors.” [Russel, Norvig 1995]
5. AI:
A three-toed sloth of genus Bradypus. This forest-dwelling animal eats the leaves of the trumpet- tree and sounds a high-pitched squeal when disturbed.(Based on the Random House Dictionary definition.)
6. Alpha-Beta Prunning:
A method of limiting search in the MiniMax algorithm. The coolest thing you learn in an undergraduate course.
7. Backward Chaining:
In a logic system, reasoning from a query to the data. See forward chaining 8. Belief Network (also Bayesian Network):
It is a mechanism for representing probabilistic knowledge. Inference algorithms in belief networks use the structure of the network to generate inference efficiently (compared to joint probability distributions over all the variables).
9. Breadth-first Search:
It is an uninformed search algorithm where the shallowest node in the search tree is expanded first.
10. Case- Based Reasoning:
Technique whereby “cases” similar to the
VIVA QUESTIONS
1. Definitions
Agent
Constraint Satisfaction
Expert system
Game playing
Genetic Algorithm and genetic programming
Knowledge acquisition
Knowledge representation
Logic programming prolog
Machine learning
Natural language processing
Robotics
Simulated annealing
Uncertainty
Vision
Search and game playing
Logic
Planning
Probabilistic reasoning
Nonmonotonic Reasoning and truth maintenance systems (TMS)
2. A*: A search algorithm to find the shortest path through a search space to a goal state using a heuristic. See ‘search’, ‘problem space’, admissibility’ and ‘heuristic’.
3. Admissibility:
An admissible search algorithm is one that is guaranteed to find the optimal path fron the start node to a goal node, if one exists. In A* search, an admissible heuristic is one that never overestimated the distance remaining from the current node to the goal.
4. Agent
“Anything that can be viewed a perceiving its environment through sensors and acting upon that environment through effectors.” [Russel, Norvig 1995]
5. AI:
A three-toed sloth of genus Bradypus. This forest-dwelling animal eats the leaves of the trumpet- tree and sounds a high-pitched squeal when disturbed.(Based on the Random House Dictionary definition.)
6. Alpha-Beta Prunning:
A method of limiting search in the MiniMax algorithm. The coolest thing you learn in an undergraduate course.
7. Backward Chaining:
In a logic system, reasoning from a query to the data. See forward chaining 8. Belief Network (also Bayesian Network):
It is a mechanism for representing probabilistic knowledge. Inference algorithms in belief networks use the structure of the network to generate inference efficiently (compared to joint probability distributions over all the variables).
9. Breadth-first Search:
It is an uninformed search algorithm where the shallowest node in the search tree is expanded first.
10. Case- Based Reasoning:
Technique whereby “cases” similar to the