AIMA 2nd Edition Chapter 2: Intelligent Agents
true
As a general rule, it is better to design performance measures according to what one actually wants in the environment, rather than according to how one thinks the agent should behave.
INFORMATION GATHERING
Doing actions in order to modify future percepts
software agents
(or software robots or softbots) exist in rich, unlimited domains.
randomize
Escape from infinite loops is possible if the agent can ____________ its actions.
definition of a rational agent
For each possible percept sequence, a rational agent should select an action that is expected to maximize its performance measure, given the evidence provided by the percept sequence and whatever built-in knowledge the agent has.
FULLY OBSERVABLE
If an agent's sensors give it access to the complete state of the environment at each point in time, then we say that the task environment is ________
learning
All agents can improve their performance through _________
partially observable
An environment might be ________ because of noisy and inaccurate sensors or because parts of the state are simply missing from the sensor data
autonomous
A rational agent should be _______-it should learn what it can to compensate for partial or incorrect prior knowledge
semidynamic
If the environment itself does not change with the passage of time but the agent's performance score does, then we say the environment is _________
deterministic
If the next state of the environment is completely determined by the current state and the action executed by the agent, then we say the environment is __________
true
In general, an agent's choice of action at any given instant can depend on the entire percept sequence observed to date.
episodic
In this task environment, the agent's experience is divided into atomic episodes.
learn
Our definition requires a rational agent not only to gather information, but also to _________ as much as possible from what it perceives
simple reflex agent
The simplest kind of agent
simple reflex agent
These agents select actions on the basis of the current percept, ignoring the rest of the percept history
ARCHITECTURE
We assume this program will run on some sort of computing device with physical sensors and actuators called _________
Goal-based agents
act to achieve their goals
rational agent
acts so as to maximize the expected value of the performance measure, given the percept sequence it has seen so far.
architecture + program
agent = _____________ + ____________
rational agent
agent that does the right thing
agent function
agent's behavior is described by the ___________
Utility-based agents
allow a comparison of different world states according to exactly how happy they would make the agent if they could be achieved
Goal-based agents
as well as a current state description, the agent needs some sort of goal information that describes situations that are desirable
true
communication often emerges as a rational behavior in multiagent environments
problem generator
component of a learning agent that is responsible for suggesting actions that will lead to new and informative experiences.
PEAS (performance measure, environment, actuators, sensors)
description of the task environment
TABLE-DRIVEN-AGENT
does do what we want: it implements the desired agent function
learning elements
element that uses feedback from the critic on how the agent is doing and determines how the performance element should be modified to do better in the future.
performance measure
embodies the criterion for success of an agent's behavior
discrete
environment that has a finite number of distinct states, also has a discrete set of percepts and actions.
continuous
environment that may be representing continuously varying intensities and locations.
task environments
essentially the "problems" to which rational agents are the "solutions."
exploration
example of information gathering
utility function
function that maps a state (or a sequence of states) onto a real number, which describes the associated degree of happiness.
INTERPRET-INPUT function
generates an abstracted description of the current state from the percept
stochastic
if the environment is complex, making it hard to keep track of all the unobserved aspects
environment class
implementations of a number of environments, together with a general-purpose environment simulator that places one or more agents in a simulated environment, observes their behavior over time, and evaluates them according to a given performance measure. Such experiments are often carried out not for a single environment, but for many environments drawn from an ___________
agent program
implements the agent function mapping percepts to actions
sequential
in these environments, the current decision could affect all future decisions.
task environment specification
includes the performance measure, the external environment, the actuators, and the sensors. In designing an agent, the first step must always be to specify the task environment as fully as possible.
agent
is anything that can be viewed as perceiving its environment through sensors and acting upon that environment through actuators
omniscience/ omniscient agent
knows the actual outcome of its actions and can act accordingly but is impossible in reality
performance element
learning agent element that takes in percepts and decides on actions
model-based reflex agents
maintain internal state to track aspects of the world that are not evident in the current percept.
Learning agents
operate in initially unknown environments and to become more competent than its initial knowledge alone might allow
Simple reflex agent
respond directly to percepts
RULE-MATCH function
returns the first rule in the set of rules that matches the given state description
environment generator
selects particular environments (with certain likelihoods) in which to run the agent.
true
simple reflex agent will work only if the correct decision can be made on the basis of only the current percept-that is, only if the environment is fully observable.
condition-action rule
some established connection in the agent program to the action
agent function
specifies the action taken by the agent in response to any percept sequence
true
stochastic behavior is rational because it avoids the pitfalls of predictability.
agent program
the agent function for an artificial agent will be implemented by an _________
Model-based reflex agents
the agent that maintain some sort of internal state that depends on the percept history and thereby reflects at least some of the unobserved aspects of the current state.
percept
the agent's perceptual inputs at any given instant
percept sequence
the complete history of everything the agent has ever perceived
reward or penalty
the performance standard distinguishes part of the incoming percept as a ________ (or________) that provides direct feedback on the quality of the agent's behavior
dynamic
these environments are continuously asking the agent what it wants to do; if it hasn't decided yet, that counts as deciding to do nothing.
static
these environments are easy to deal with because the agent need not keep looking at the world while it is deciding on an action, nor need it worry about the passage of time.
utility-based agents
try to maximize their own expected "happiness."
function UPDATE-STATE
which is responsible for creating the new internal state description