Artifical Intellegence Final

Beschreibung

Flash cards to help prep for AI final
Thomas Scott
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Thomas Scott
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Zusammenfassung der Ressource

Frage Antworten
Agent Anything that can be viewed as perceiving its environment through sensors and acting upon that environment through actuators
Agent Program Physical architecture that instantiates an agent function
Rational Agent Maximizes the expected value of a performance measure given the observed percept sequence
Mode-based Agent Maintains an internal representation of the world for reasoning in partially observable environments
Utility-based Agent Selects appropriately between several goals based on likelihood of success
Goal-based Agent Reasons about future actions in order to reach a desirable outcome
Agent Function Maps percept histories into actions
Random Actions Useful for exploring unknown environments
Turing Test Requires natural language processing and automated reasoning
During Classical search, nodes which are queued for expansion are part of the _______ region of the search space, while nodes which have been expanded are part of the _______ region 1) frontier 2) explored
True or False: In classical search methods, the search strategy determines the order in which nodes are expanded during the search process. True
In complexity theory, _________ problems are a subset of problems in NP to which any problem in NP can be reduced in __________ time. 1) NP complete 2) P
The PEAS acronym stands for ________, _________, ___________, and _________ 1) Performance 2) Environment 3) Actuators 4) Sensors
True or False: Any solution found by greedy best-first search must be optimal False
Explain the difference between uniformed search strategies and informed search strategies Uninformed strategies do not care how the goal is achieved, while informed strategies take heuristic estimates into consideration
What are the "four corners" of AI Thinking Humanly Acting Humanly Thinking Rationally Acting Rationally
What does it mean for a heuristic to be admissible? It has to be less than the actual cost and is optimistic
What does it mean for a heuristic to be consistent(monotonic)? f always increases along any path to the goal
What does it mean for a heuristic to be dominant over an alternative heuristic? h2(n) >= h1(n) for all n and both are admissible
Describe a search space in which Iterative Deepening Search performs better than Depth-First search If there is an infinte deapth IDS would be better.
Describe when and why Iterative Deepening Search would be preferred over Breadth First Search for some search problems. When space is limited, IDS is the better option
Explain when and why using a closed list for A* Search is not preferred for some search problems If h(n) is inconsistent it would lead to sub optimal solution
Describe a problem environment that is partially observable. The game battleship
Describe a problem where the environment is fully observable, but the agent is unable to perform optimally In a dynamic environment, even if the environment is fully observable, the agent can not perform optimally
Suppose there is an environment in which a rational agent selects actions from a learned probability distribution (based on its past experience with the environment). Is this an example of a problem with stochastic environments? [Fill in later]
Suppose a learning agent is asked to solve a task multiple times, starting over from the same initial state each time. Is this an example of an episodic environment or sequential environment? Episodic
How could you transform an episodic environment into a sequential environment? You could add an element of time to make the environment sequential. (From slot machine example) Instead of the environment resetting every time the handle is pulled, the environment would consist of many pulls
Multi-agent environments give rise to (at least) two kinds of interactions among the agents that are not found in single-agent environments. Name two interactions and describe why they are advantageous/disadvantageous from an agent's perspective 1) Adversarial, agents must act against one another. This can be used to help agents learn. Example: Two agents learning chess by playing one another 2) Cooperative, agents must work together to complete a task. This can help up the effectiveness of completing a task
Use the four steps of problem formulation to explicitly define the problem faced by a vacuum-cleaner agent in an environment with exactly two locations. 1) Check the state 2) Check the actions 3) Check the goal 4) Check step costs
What are some common problems with greedy local search? It can get stuck on plateaus and local maxima
How does simulated annealing attempt to solve the common problems with greedy local search? It allows for bad moves
How is the temperature parameter in simulated annealing used to aid exploration? [Fill In]
What are three mechanisms used by genetic algorithms to overcome the problems of greedy local search? 1) mutation 2) selection 3) cross over
What is the fundamental difference between the local search approaches above, and the classical search methods (DFS, A*, etc) that we studied earlier in the semester? Only concerned with finding a goal/solution in local search instead of a path which is the aim of classical search
What is the horizon effect in adversarial search? At some point a search has a max depth, and cannot see past a horizon
What happens when we are playing a game using the minimax algorithm and the opponent (MIN) makes a non- optimal move? This lets the player(MAX) makea better move
Give an example of a valid sentence in propositional logic p v -p
Give an example of an unsatisfiable sentence in propositional logic p <=> -p
Is the sentence (-(-Smoke => -Fire) => (Fire => Smoke)) valid, unsatisfiable , or satisfiable ? satisfiable
Linear regression is an example of parametric or nonparametric model? parametric
True or False: When constructing a non-parametric model, the required number of basis vectors or functions can be determined directly from the raining data False
True or False: Non- parametric models may be constructed using an arbitrary number of parametric models. True
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