文档介绍：Introduction to Artificial Intelligence
Intelligent Agents
Bernhard Beckert
UNIVERSITÄT KOBLENZ-LANDAU
Winter Term 2004/2005
B. Beckert: KI für IM –
Outline
Agents and environments
PEAS (Performance, Environment, Actuators, Sensors)
Environment types
Agent types
Example: Vacuum world
B. Beckert: KI für IM –
Agents and environments
sensors
percepts
?
environment
agent
actions
actuators
Agents include
– humans
– robots
– software robots (softbots)
– thermostats
– etc.
B. Beckert: KI für IM –
Agent functions and programs
Agent function
An agent pletely specified by the agent function
f : P ∗→ A
mapping percept sequences to actions
B. Beckert: KI für IM –
Agent functions and programs
Agent program
runs on the physical architecture to produce f
takes a single percept as input
keeps internal state
function SKELETON-AGENT(percept) returns action
static: memory /* the agent’s memory of the world */
memory ← UPDATE-MEMORY(memory, percept)
action ← CHOOSE-BEST-ACTION(memory)
memory ← UPDATE-MEMORY(memory,action)
return action
B. Beckert: KI für IM –
Note
rational 6= omniscient
rational 6= clairvoyant
rational 6= essful
Agents need to: gather information, explore, learn, . . .
Rationality
Goal
Specified by performance measure,
defining a numerical value for any environment history
Rational action
Whichever action maximizes the expected value
of the performance measure given the percept sequence to date
B. Beckert: KI für IM –
Agents need to: gather information, explore, learn, . . .
Rationality
Goal
Specified by performance measure,
defining a numerical value for any environment history
Rational action
Whichever action maximizes the expected value
of the performance measure given the percept sequence to date
Note
rational 6= omniscient
rational 6= clairvoyant
rational 6= essful
B. Beckert: KI für IM –
Rationality
Goal
Specified by pe