introduction to agents and multi-agent systems (lecture slides)

D. Monett – Europe Week 2014, University of Hertfordshire, Hatfield

Introduction to Agents and

Multi-agent systems

Prof. Dr. Dagmar Monett Díaz Computer Science Dept.

Faculty of Cooperative Studies

Berlin School of Economics and Law

[email protected]

Europe Week, 3rd – 7th March 2014

D. Monett – Europe Week 2014, University of Hertfordshire, Hatfield 2

Two “intelligent” agents…


Dilbert

Scott Adams

At http://dilbert.com/strips/comic/1991-02-08/

(Educational/Classroom usage permission is granted by Universal Uclick. All Rights Reserved)

“Intelligent” travel agent #1

3

http://dilbert.com/strips/comic/1991-02-08/






Dilbert

Scott Adams



“Intelligent” travel agent #2

4







Another kind of “intelligent” agent


Travel agent: simple case

"Stimulus-response„ search engine

Customer: Agent:

Specifies request with preferences

[Fill out form]

Specifies answer

[Show matching

offers]

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Travel agent: more complex

Customer: Agent:

I want to go on vacation

Wonderful!

Do you like

swimming?

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Customer: Agent:

Yes, with good friends on a white beach. And I like sports.

Wonderful!

And in the evening?

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Customer: Agent:

Good entertainment, exclusive bars, etc.

Sounds fantastic. Is this what you are looking for? [Present an offer]

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Customer: Agent:

Really fantastic but over my budget. I‘d prefer something less exclusive...

Let's see… How about this? [Present a new offer]

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What would that agent need for the

dialog?



12

Such a travel agent would need its knowledge to be

dynamic:



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dynamic:

Dialog history



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dynamic:

Dialog history

(Hypothetical) model of the customer’s and own

• desires, intentions

• preferences, opinions



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dynamic:

Dialog history

(Hypothetical) model of the customer’s and own

• desires, intentions

• preferences, opinions

(Flexible) plan for

• exploring the customer’s desires and intentions

• profitable offers


Agenda


Agenda

Where does the major content come from?

What is an agent? What is a multi-agent system?

Agent types

Agent properties

Design of intelligent agents

Implementing practical reasoning agents

Further reading, sources of inspiration, and more…


©


An Introduction to

MultiAgent Systems

Michael Wooldridge

2nd Edition, 484 pp.

John Wiley & Sons, May 2009

ISBN-13: 978-0470519462

With materials available at

http://www.csc.liv.ac.uk/~mjw/pub

s/imas/IMAS2e.html

What I also use in my lectures at the HWR…

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http://www.csc.liv.ac.uk/~mjw/pubs/imas/IMAS2e.html

http://www.csc.liv.ac.uk/~mjw/pubs/imas/IMAS2e.html


Artificial Intelligence: A

Modern Approach

Stuart Russell and Peter Norvig

3rd Edition, 1152 pp.

Prentice Hall, December 2009

ISBN-13: 978-0136042594

With materials available at

http://aima.cs.berkeley.edu/

What I also use in my lectures at the HWR…

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“The AI Bible”

http://aima.cs.berkeley.edu/


What is an agent?


Agents, a definition

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According to Michael Wooldridge:

“An agent is a computer system that is

capable of independent action on behalf of

its user or owner (figuring out what needs to

be done to satisfy design objectives, rather

than constantly being told)”.



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“The main point about agents is they are

autonomous: capable of acting

independently, exhibiting control over their

internal state.

Thus: an agent is a computer system

capable of autonomous action in some

environment in order to meet its design

objectives”.



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According to Russell and Norvig:

“An agent is anything that can be viewed as

perceiving its environment through sensors

and acting upon that environment through

actuators”.


Agents

Agents communicate with the environment

through Sensors and Actuators


What is a multi-agent system?


Dilbert

Scott Adams



Agent in a group

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Multi-agent systems, a definition

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“A multi-agent system is one that consists of

a number of agents, which interact with one-

another”.


Multi-agent systems, a definition

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“A multi-agent system is one that consists of

a number of agents, which interact with one-

another”.

In the most general case, agents will be acting on

behalf of users with different goals and motivations

To successfully interact, they will require the ability

to cooperate, coordinate, and negotiate with each

other, much as people do


Agent types


Agent types

Four basic types in order of increasing

generality:

Simple reflex agents

Model-based reflex agents

Goal-based agents

Utility-based agents

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Simple reflex agents


Model-based reflex agents


Goal-based agents


Utility-based agents


Learning agents


Dilbert

Scott Adams



A real state agent

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Agent properties


Intelligent agents are…

reactive

pro-active

social

rational

benevolent

adaptable

truthful

autonomous

mobile

A reactive system is one that

maintains an ongoing interaction

with its environment, and responds

to changes that occur in it (in time

for the response to be useful).

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reactive

pro-active

social

rational

benevolent

adaptable

truthful

autonomous

mobile

Pro-activeness = generating and

attempting to achieve goals; not

driven solely by events; taking the

initiative; recognizing opportunities.

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reactive

pro-active

social

rational

benevolent

adaptable

truthful

autonomous

mobile

Social ability in agents is the ability

to interact with other agents (and

possibly humans) via some kind of

agent-communication language, and

perhaps cooperate with others.

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reactive

pro-active

social

rational

benevolent

adaptable

truthful

autonomous

mobile

An agent should strive to do the

right thing, based on what it can

perceive and the actions it can

perform. The right action is the one

that will cause the agent to be most

successful.

An agent will act in order to achieve

its goals, and will not act in such a

way as to prevent its goals being

achieved – at least insofar as its

beliefs permit

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reactive

pro-active

social

rational

benevolent

adaptable

truthful

autonomous

mobile

Agents do not have conflicting

goals. Every agent will therefore

always try to do what is asked of it.

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reactive

pro-active

social

rational

benevolent

adaptable

truthful

autonomous

mobile

Agents improve performance over

time. They can learn.

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reactive

pro-active

social

rational

benevolent

adaptable

truthful

autonomous

mobile

An agent will not knowingly

communicate false information

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reactive

pro-active

social

rational

benevolent

adaptable

truthful

autonomous

mobile

An agent is autonomous if its

behaviour is determined by its own

experience (with ability

to learn and adapt)

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reactive

pro-active

social

rational

benevolent

adaptable

truthful

autonomous

mobile

Mobility: the ability of an agent to

move around an electronic network

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Design of intelligent agents.

Examples


Settings

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Performance measure

Environment

Sensors

Actuators


Settings

50

Performance measure

Environment

Sensors

Actuators

Designing an automated taxi driver:

Safe, fast, legal, comfortable trip, maximize profits

Roads, other traffic, pedestrians, customers

Cameras, speedometer, GPS, engine sensors, keyboard, etc.

Steering wheel, accelerator, brake, signals


Settings

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Performance measure

Environment

Sensors

Actuators

Designing a medical diagnosis system:

Healthy patient, minimize costs, lawsuits

Patient, hospital, staff

Keyboard (entry of symptoms, findings, patient's answers)

Screen display (questions, tests, diagnoses, treatments, referrals)


Settings

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Performance measure

Environment

Sensors

Actuators

Designing an interactive English tutor:

Maximize student's score on test

Set of students

Keyboard

Screen display (exercises, suggestions, corrections)


Active learning exercise:

“How to implement

reactive agents?

Discuss it with your classmates!”

Image © renjith krishnan at http://www.freedigitalphotos.net/


Implementing deliberative agents.

First steps.


Agent Control Loop Version 1 while true observe the world; update internal world model; deliberate about what intention to achieve next; use means-ends reasoning to get a plan for the intention; execute the plan end while

First pass


More formally…


With deliberation…

[…which can be further extended to consider practical reasoning agents…]


Dilbert

Scott Adams



The real state agent (cont.)

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Homework:

“Search for real-world applications

that use intelligent agents and

describe their tasks and

functioning!”



Assessment



Question

61

(Taken from a public sample exam © Wooldridge)

Briefly define and explain, with examples where

appropriate, THREE properties you would

expect an intelligent agent to exhibit!

PLEASE ANSWER AT:

https://docs.google.com/forms/d/1K0RZur9bDtZs0R0k74GKn7Va34ALPYtXxXUFJH51_1k/viewform

https://docs.google.com/forms/d/1K0RZur9bDtZs0R0k74GKn7Va34ALPYtXxXUFJH51_1k/viewform


Last active learning exercise



The content


References


Others…

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Further reading and sites…

IFAAMAS – International Foundation for

Autonomous Agents and Multiagent Systems

http://ifaamas.org/

Journal Autonomous Agents and Multi-Agent

Systems

http://link.springer.com/journal/10458

13th International Conference on Autonomous

Agents ans Multiagent Systems (AAMAS’14), Paris,

France

http://aamas2014.lip6.fr/

66

http://ifaamas.org/

http://link.springer.com/journal/10458

http://aamas2014.lip6.fr/


Slides of the talk per request:

[email protected]

Prof. Dr. Dagmar Monett Díaz

monettdiaz

@dmonett

http://monettdiaz.com

introduction to agents and multi-agent systems (lecture slides)

Education

monett europe week

university of hertfordshire

hatfield travel agent

intelligent travel agent

hatfield agents

hatfield introduction

kind of intelligent

multiagent system