Agent |
Entity that perceives, reasons and acts
within some external environment (e.g., intelligent agent). |
Alpha-Beta pruning |
Method for improving the efficiency of
minimax search used for game playing systems. |
Autonomous |
Able to function without external control
or intervention (e.g., au­tonomous agent; autonomous mobile
robot). |
Backpropagation |
A learning
algorithm used for neural networks. |
Backtracking |
Returning to a previous choice point
in a search, in order to explore other alternatives. |
Backward chaining |
Method used in problem solving which
involves starting with a goal or hypothesis and working backwards
using rules to find what facts are necessary to prove the goal. |
Bayes theorem |
Rule for calculating the probability
of a hypothesis given some evidence, based on other available
probabilities. |
Best first |
Search strategy which uses heuristics
to guide search, looking at the most promising nodes first. |
Breadth first |
Search strategy that involves exploring
all nodes in a tree at a given depth (from root) before exploring
nodes further down in tree. |
Brute force |
Search strategy not using any intelligence
or heuristics. |
Case-specific data |
Data specific to a particular problem
or case (e.g., data on a particular patient) in an expert system. |
Certainty factors |
Measure of the likelihood that a fact
or conclusion is true, often used in rule-based expert systems. |
Chinese room |
Thought experiment proposed by Searle
to demonstrate that a sys­tem could behave intelligently
without being intelligent. |
Class |
Group of items with similar characteristics. |
Classification |
Assigning an object to a particular category
or class based on its features. |
Combinatorial explosion |
Term used to indicate a problem with
exponential com­plexity, where increasing the size of a problem
by a small amount causes an explosion in the number
of possibilities to be considered when looking for a solution. |
Multiple inheritance |
Inheritance from several different sources
(when a class may have multiple parents). |
Natural language |
A human language (like English) rather
than a computer lan­guage. |
Parse tree |
Tree representation of syntactic structure
of sentence. |
Pattern recognition |
Class of methods for identifying the
category to which an object belongs based on its (often visual)
pattern (e.g., identifying letters in handwriting from an image). |
Perceptron |
Simple
neural network. |
Phoneme |
Basic
unit of speech; part of word (e.g., t). |
Pixel |
Point-like,
basic element of a digital image. |
Pragmatics |
Stage of language analysis that takes
account of the context in which things are said. |
Predicate logic |
A logic widely used in Al for representing
knowledge. |
Procedural |
Representing how something should
be done (procedures) rather than what is true (cf. Declarative). |
Production rule |
Term used for IFTHEN rules in rule-based
expert systems. (Meaning of term slightly different in other
areas of Computer Science.) |
Proof theory |
Theory stating what inferences are valid
in a logic. |
Reason maintenance |
Recording the justifications for conclusions,
so when a fact is withdrawn all the facts that are derived from
it are also withdrawn. |
Representational
adequacy |
Ability
to represent complex facts. |
Resolution |
A rule of inference and simple proof
procedure based on that rule of inference. Used in the Prolog
programming language. |
Robot |
System able to manipulate physical objects
in the world, usually with the aid of sensors. |
Rule-based system |
Expert system based on using IFTHEN
rules for represent­ing knowledge. |
Search space |
Set of all possible nodes to be considered
in a given search problem (usually those reachable from some
start node). |
Search strategy |
Strategy for controlling the search (of
a graph or tree) for some target node or state. |
Search tree |
Tree representation of search space,
showing how possible solutions may be reached from some initial
state. |
Semantic network |
Knowledge representation scheme based
on networks of nodes and links, normally representing objects
and relationships between objects. |
Semantics |
The meaning of a statement (whether a
natural language sentence, statement in a programming language,
or statement in a logic). Also used to refer to the stage of
natural language understanding concerned with deriv­ing sentence
meaning. |
Speech act |
Action performed by spoken utterance
(e.g., command). |
Speech
recognition |
The recognition
of word sequences from a speech signal. |
Speech
understanding |
Determining
sentence meaning from a speech signal. |
State space |
Set of problem states reachable, given
a problem to be solved using state space search. |
State space search |
Solving a problem by searching through
the possible problem states that may be reached from some initial
state. |
Subsymbolic |
Representation of knowledge such that
there are no meaningful symbol structures (e.g.,
neural networks). |
Symbol structures |
Data structures composed of symbols denoting
objects or con­cepts. Most Al knowledge is represented in
this way. |
Syntax |
Legal organizations of constituents in
a language. For example, the syntax of English defines legal
combinations of words in a sentence. Also used to refer to stage
of natural language understanding concerned with ascertaining
the structure of a sentence. |
Turing test |
Test proposed to check for human-like
intelligence by comparing a computer programs ability to
answer arbitrary questions with that of a human. |
Version space learning |
Inductive learning method based on a
particular algo­rithm for searching a space of hypotheses. |
Working memory |
Part of expert system used to represent
facts that are currently believed true about the problem being
worked on. |