Lecture 19 - Intelligent Agents

Question 1

What is an agent?

Answer 1

A system that is situated in an environment

Capable of autonomous action in the environment to achieve goals or design objectives

Question 2

What does autonomous imply in relation to intelligent agents?

Answer 2

The agent can act without the intervention of humans or other agents

Question 3

What must agents be able to do?

Answer 3

Perceive/Understand their environment

Act upon their environment

Question 4

A central heating thermostat is an example of an agent. What is the environment, sensor and actions of the agent?

Answer 4

Environment: Building whose heating it regulates

Sensor: Its temperature sensor

Actions: Turn heating on, Turn heating off

Question 5

A pressure cooker safety valve is an example of an agent. What is the environment, sensor and actions of the agent?

Answer 5

Environment: Pressure cooker and its surroundings

Sensor: Pressure sensor

Actions: Open valve, Close valve

Question 6

A simple spinal withdrawal reflex is an example of an agent. What is the environment, sensor and actions of the agent?

Answer 6

Environment: Animal’s body and surroundings

Sensor: Pain sensors in the skin

Actions: Activate flexor muscles

Question 7

When is an agent considered to be intelligent?

Answer 7

When it is capable of flexible autonomous behaviour

Question 8

What does flexible mean in the context of autonomous behaviour and intelligent agents?

Answer 8

Pro active

Conditionally reactive

Socially interactive

Question 9

What does pro-active mean in the context of flexible autonomous behaviour?

Answer 9

Can take the initiative in order to achieve goals

Question 10

What does conditionally reactive mean in the context of flexible autonomous behaviour?

Answer 10

Can react in a timely fashion to changes in the environment by selecting the appropriate response from a range of alternatives

Question 11

What does socially interactive mean in the context of flexible autonomous behaviour?

Answer 11

Can interact with other agents (possibly including humans) to achieve collective goals

Question 12

Why are expert systems generally not considered to be intelligent agents?

Answer 12

They do not perceive their environment directly - needs a human user

Do not act on the environment - give advice to the user instead

Question 13

What are two types of intelligent agents?

Answer 13

Reactive agents

Agents with internal state

Question 14

How do reactive agents make decisions?

Answer 14

Direct mapping from current situation to action:

S->A

No memory of earlier environment states

Question 15

Markov Decision Process is an example of which type of intelligent agent? why?

Answer 15

Reactive agent

Does not usually use memory to retain previous states

Question 16

What separates an agent with internal state from a purely reactive agent?

Answer 16

Agents with internal state have some form of memory that future actions are based on.

Reactive agent just maps states to actions

Internal state:

agent_see: SxM -> M

agent_act: M -> A

Question 17

What are the three main motivations of research into reactive agents?

Answer 17

Approaches based on manipulation of symbolic representations were not well accepted

Intelligent behaviour should be viewed as product of interaction between agent and environment

Intelligent behaviour emerges from interaction of a number of simpler behaviours

Question 18

What is the Subsumption Architecture?

Answer 18

A reactive agent architecture

Question 19

What are the two main ideas of subsumption architecture?

Answer 19

Task accomplishing behaviours - decision making realised through set of simple responses to current state

Subsumption Hierarchy - behaviours arranged in layers, lower layers inhibit higher layers - so as you go down the actions get more specialised

Question 20

What are the advantages of reactive architectures in intelligent agents?

Answer 20

Cheap - low computational power required

Robust - loss of single agent does not seriously disrupt operation of entire set

Question 21

What are the disadvantages of reactive architectures in intelligent agents?

Answer 21

All decisions based on purely local info so must gather good info to make good decisions

All behaviours are short term - no memory

Emergent behaviour difficult to program

Question 22

What does BDI stand for, and what is it?

Answer 22

Belief-Desire-Intention

A type of agent with internal state

Question 23

In multi-agent systems, what are the two types of interaction and what does each involve?

Answer 23

cooperation - must construct plans to achieve collective goals, either centrally or distributed

competition - must negotiate to resolve conflicts

Question 24

What are the two types of communication in multi agent systems?

Answer 24

Direct communication - agents exchange mssages with each other

Indirect communication - agents communicate by acting on the environment