CSE 3521 Midterm 1

Open set for DFS

Stack

Open set for DLS

Stack where nodes at the limiting depth have no successors

Open set for IDS

Stack where nodes at the limiting depth have no successors

An inference procedure is complete if we can...

find a proof for any sentence that is entailed

If entailment is knowing that the needle is in the haystack, then inference is....

finding it

Agent = Architecture + Program

Architecture is the computing device + Program implements the agent function mapping of percepts to actions

Minimax algorithm

Determines the best move for some agent MAX taking into account it's playing against some agent MIN which attempts to minimize its score

Sensors

Devices that collect input from the environment and provide information that the CPU can respond to.

Four categories of AI:

(1) Thinking humanly, (2) Thinking rationally, (3) Acting humanly, (4) Acting rationally

Two central AI concepts

(1) how we represent knowledge and (2) how we reason with it

A problem is defined by four items...

(IsGAP) - Initial state, goal test, actions, path cost

PEAS description

- (P)erformance Measure - (E)nvironment - (A)cutators - (S)ensors

A simple knowledge based agent needs to know what?

- current state of the world - how to infer things from percepts - how world evolves over time - what its goal is - what actions to take in various circumstances

Rationality is concerned with...

...expected success given what has been perceived

Define rationality

A "rational" system "does the right thing" whereas humans make mistakes

Admissible Heuristic

A heuristic that never overestimates the cost to reach the goal.

Problem-solving agent

A kind of goal-based agent that decides what to do by finding sequences of actions that lead to desirable states

Proof

A record of inference procedure operations

A solution is...

A sequence of operators leading from the initial state to a goal state

Turing Test

A test proposed by Alan Turing in which a machine would be judged "intelligent" if the software could use conversation to fool a human into thinking it was talking with a person instead of a machine.

Performance measure

A way to evaluate the agent's success

Effectors

Affects the environment

Percept

Agent's perceptual inputs at any given instant

Agent/Robot

An Agent is anything that perceives its environment through sensors and acts upon that environment through effectors.

Rational agent

An agent which does the right thing

Skolem constant

Arbitrary substitution for a there exist statement's variablee

Game

Any multi-agent environment (Life is a game)

Time Complexity ordering across algorithms

BFS < IDS < DLS< Minimax w/ pruning, DFS = Greedy A* depends a lot on heuristic

Optimality across algorithms

BFS: yes UCS: ehhh its okay DFS: no DLS: no IDS: yes Greedy: no Minimax w/o pruning: yes Minimax w/ pruning: optimal against optimal component, even more optimal against non-optimal component A*: yes

Completeness across algorithms

BFS: yes UCS: yes DFS: no DLS: yes if depth limit big enough, no otherwise IDS: yes Greedy: no Minimax w/o pruning: yes Minimax w/ pruning: yes A*: yes

Autonomous behavior

Behavior is determined by its own experience

Strong AI view

Build a mind in a computer

Knowledge

Codified experience of agents

Thinking humanly

Cognitive science. Requires understanding of the human brain (which can either be top-down = from the behavior to the rationale or bottom-up = from the neurological data to the behavior)

Percept "sequence"

Complete history of everything an agent has perceived

Simple reflex agents

Condition-action rules on current percept

What are the four stages of a problem solving agent?

Decide on goal, formulate problem, search, execute solution

"Society of mind"

Each mind is made of many smaller agents

Dynamic

Environment can change while agent is thinking

Static

Environment doesn't change while agent is thinking

Agent environments

Environments that are partially observable, stochasic, sequential, dynamic, continuous, and multi-agent are HARDEST to model

Episodic

Everything is its own atomic moment and the state of one episode doesn't affect the state of hte next

Ideal Rational Agent

For each possible percept sequence, do whatever action is expected to maximize its performance measure, using evidence provided by the percept sequence and any built-in knowledge

Causal rule

From causes to effects

Diagnostic rule

From effects to causes

Uninformed search

Given no information about problem (other than its definition)

Informed search

Given some idea of where to look for solutions (outside intuition)

An optimal solution...

Has lowest path cost

Space complexity ordering across algorithms

IDS < DLS < DFS < BFS < UCS

Monotonic

If new sentences are added to KB, all sentences entailed by original KB are still entailed by new KB

Non-autonomous behavior

If no use of percepts then system has no autonomy

Agent program

Implements the agent function for an agent

Learning agents

Improves over time

Weak AI view

Not a mind, but good intelligent process

What are the two things that make up a state space?

Initial state + actions available

Why is AI difficult?

Intelligence is not very well defined or understood

What is intelligence?

Intelligence is the computation part of the ability to achieve goals in the world

What is Artificial Intelligence?

It is the science and engineering of making intelligent machines, especially intelligent computer programs.

Stochastic

Not deterministic

Thinking rationally

Logic. What are correct reasoning processes?

Utility-based agents

Maximizes agent's happiness

KB | - i gets us a

Means that a is derived from KB by inference i

Multi-agent

Multiple agents to worry about

Expert

Narrow specialization and substantial competence

For all x there exists y

Needs skoklem function SK1(x) to get us the y, since they could be different and varied y

Are all admissible heuristics consistent?

No

Omniscience

Omniscient agent knows actual outcome of its actions and can act accordingly

Entailment

One fact follows logically from another

Single agent

Only one agent to worry about

a >= b

Only safe for earliest move strategies of Minimax

Discrete

Operations are distinct and separate

Continuous

Options are not distinct and separate (moving through real values)

AI has so many ****ing foundations

Philosophy, mathematics, economics, neuroscience, psychology, computer science, control theory and cybernetics, computational linguistics

Logic

Precisely defined syntax and semantics for a knowledge representation language

Open set for UCS

Priority queue

Open set for BFS

Queue

Acting rationally

Rational behavior = doing the right thing. Doesn't necessarily involve thinking (i.e., hot stove reflexes)

What two things do we need to make inferences?

Representation and reasoning. The point of our AI is to make inferences, so it needs the representation of the knowledge and the reasoning processes acting on the knowledge

For expressing knowledge as a language, we need what two things?

Semantics and syntax, just like any language

Partially observable

Sensors do not give complete state of environment at each time point

Fully observable

Sensors give complete state of environment at each time point

Why have a knowledge base?

So we can tell it things which we can ask it later (kind of like your mom)

Agent function

Specifies which action to take in response to any given percept sequence

Sequential

States bleed over and affect each other

Consistent Heuristic

The difference between connected states is always smaller than or equal to the actual cost

Deterministic

The next state of the environment is completely determined by current state + action of the agent

Categorization

Treat different things as equivalent - respond in terms of class membership rather than individually. Reduces complexity.

The Knowledge Hypothesis

To achieve a high level of problem solving competency, a symbol system must use a great deal of domain, task and case specific knowledge

Goal-based agents

Uses goals and planning to make a decision

Acting humanly

Turing Test. Making a human imitate a computer

Who is involved in building knowledge systems?

Users, experts, and knowledge engineers

Model-based reflex agents

Watches as a model evolves over time

What is the "right thing/rational action"?

Whichever action that will cause the agent to be most successful (we need a way to measure success)

Are all consistent heuristics admissible?

Yes

Is knowledge definite for logical agents?

Yes

Does AI aim at human-level intelligence?

Yes!

Steps of a problem-solving agent

[Step 1] Formulate goal [Step 2] Formulate problem [Step 3] Search [Step 4] Execution phase [Step 5] Find a new goal (repeat)

A sentence is valid if...

it's a tautology

A sentence is satisfiable if...

its true in some instance

To move a particular constant outwards we can use...

negation