Artificial Intelligence Midterm

What is used to judge search algorithms

- completeness - optimality - time complexity - space complexity

What the five components of a problem?

- initial state - actions - transition model - goal state - path cost

Which of the following disciplines contribute to AI?

- philosophy - mathematics - economics - neuroscience - cognitive science - linguistics - machine learning - control theory - computer engineering

What is AI?

- thinking humanly - acting humanly - thinking rationally - acting rationally

With respect to search strategies, DFS stands for

Depth-first search

T/F: Informed search methods have access only to the problem definition.

False

T/F: A rational agent is one that acts randomly in an environment, regardless of expected outcome.

False, A rational agent is one that acts to achieve the best expected outcome.

T/F: An agent function and an agent program are the same thing.

False, An agent function is an abstract mathematical mapping from percept sequences to actions; an agent program is a specific implementation in a system.

T/F: An agent that senses only partial information about the state cannot be perfectly rational.

False, Perfect rationality refers to the ability to make good decisions given the sensor information received.

T/F: Propositional logic assumes the world consists of objects, relations, and functions

False, Propositional logic assumes the world contains facts that are true or false.

T/F: A supermarket bar code scanner is an example AI system.

False, The problem of reading a bar code is an extremely limited and artificial form of visual interpretation, and it has been carefully designed to be as simple as possible, given the hardware.

T/F: A game of Battleships is fully observable

False, a game of Battleships is partially observable

T/F: A game of Monopoly is deterministic

False, a game of Monopoly is Stochastic.

T/F: The term two-ply refers to the thickness of the game pieces

False, a ply is simply considered to be one turn by a player

T/F: World state and state description are the same thing.

False, a world state is how reality is or could be. A state description is an agent's internal description of a world state.

T/F: Existential Quantification is equivalent to the conjunction of all possible instantiations

False, equivalent to the disjunction of all possible instantiations

T/F: DFS expands the shallowest nodes first

False, expand deepest unexpanded node.

T/F: Straight Line Distance (SLD) is the same thing as Manhattan Distance.

False, straight line distance surface is used to find the shortest distance, a straight line, from each cell to the closest source. Manhattan distance is the distance between two points measured along axes at right angles.

T/F: The following is a correct English sentence of the logical sentence ∀x At(x,Howard) ⇒ Smart(x): Someone at Howard is smart .

False, ∀x implies ALL students

T/F: The following is a correct English sentence of the logical sentence ∃x At(x,Howard) ⇒ Smart(x): Everyone at Howard is smart .

False, ∃x implies SOME students.

____________________ chaining is proving new things and adding them to the KB until we can prove q.

Forward

T/F: The input to an agent program is different than the input to the agent function.

True, The agent function, notionally speaking, takes as input the entire percept sequence up to that point, whereas the agent program takes the current percept only

T/F: The sentence ∀ x P(x) ∨ ¬P(x) is valid.

True, for any relation denoted by P, every object x is either in the relation or not in it.

T/F: h(n) = 0 is an admissible heuristic for the 8-puzzle.

True, h(n)=0 NEVER over-estimates the remaining optimal distance to a goal node.

The _____________________ Test is used to assess artificial intelligence in computing machinery.

Turing

Successor function

a function that generates a next state from the current state, plus the choices that affect state changes.

State space

a graph whose nodes are the set of all states, and whose links are actions that transform one state into another.

State

a situation that an agent can find itself in. We distinguish two types of states: world states (the actual concrete situations in the real world) and representational states (the abstract descriptions of the real world that are used by the agent in deliberating about what to do).

Learning agent

a tool in AI that is capable of learning from its experiences. It starts with some basic knowledge and is then able to act and adapt autonomously, through learning, to improve its own performance.

Utility-based agent

an agent that acts based not only on what the goal is, but the best way to reach that goal.

The ____________ factor in a search tree is the number of actions (successor nodes) available to the agent at a given node

branching

Model-based agent

can work in a partially observable environment, and track the situation.

Minimax strategy

choosing the moves that gives the best worst-case payoff

________________ science focuses on the brain as an information processing machine

cognitive

Inference

deriving sentences from other sentences

alpha-beta search algorithm

eliminating subtrees that are provably irrelevant

Goal-based agent

expands on the concept of model-based agents, which understand the world around them by implementing the desired outcome or goal to be reached. A goal-based agent takes it a step further by using a goal in the future to help make decisions about how best to reach that outcome.

Syntax

formal structure of sentences

Goal

is a state that the agent is trying to reach.

KB stands for ______________________________

knowledge base

Entailment

necessary truth of one sentence given another

Reflex-agent

performs actions based on a current situation.

Action

something that the agent can choose to do.

what is the state space of a problem

the initial state, actions, and transition model

Evaluation function

the probability of winning from a given state

Minimax value of a node

the utility of being in the corresponding state

Semantics

truth if a sentence with respect to models

What is the symbol for the Universal Quantifier?

∀x

What is the symbol for the Existential Quantifier?

∃x

T/F: A chess game is fully observable

True

T/F: A game of Poker is Stochastic

True

T/F: A heuristic function h(n) estimates the cost of a solution from Node n

True

T/F: A search strategy is defined by picking the order of node expansion.

True

T/F: A* search expands nodes with minimal f(n) = g(n) + h(n).

True

T/F: BFS expands the shallowest nodes first

True

T/F: First Order logic assumes the world consists of objects, relations, and functions

True

T/F: Greedy best-first search expands nodes with minimal h(n).

True

T/F: Uninformed search methods have access only to the problem definition.

True

T/F: Universal Quantification is equivalent to the conjunction of all possible instantiations

True

T/F: The search tree for a chess game is 10^154 nodes

True, In chess, branching factor ≈ 35 and depth ≈ 100, giving a search tree of 10^154 nodes.

T/F: Strong AI is making a system that thinks like a human

True, Strong Artificial Intelligence (AI) is a theoretical form of machine intelligence that is equal to human intelligence.

_____________________ chaining is finding p1,. . . , pn such that knowing them would prove q

Backward

With respect to search strategies, BFS stands for

Breadth-first search

What is the correct English sentence for: ∀c Country(c) ∧ Border(c,Ecuador ) ⇒ In(c,SouthAmerica)?

All countries that border Ecuador are in South America.

Which of the following is the correct truth table for P Λ Q ?

P | Q | P Λ Q F | F | F F | T | F T | F | F T | T | T

What is the correct English sentence for: In(Paris,France ) ∧ In(Marseilles,France)?

Paris and Marseilles are both in France.

With respect to intelligent agents, what does PEAS stand for?

Performance measure, Environment, Actuator, Sensor

What is the correct English sentence for: ∃c Country(c) ∧ Border(c,Iraq) ∧ Border(c,Pakistan)?

There is a country that borders both Iraq and Pakistan.