Introduction to Autonomous Agents
and Multi-Agent Systems
Lecture 1
The Unit....
• Theoretical lectures: Tuesdays (Tagus), Thursdays
(Alameda)
• Evaluation:
– Theoretic component: 50% (2 tests).
– Practical component: a project (2-3 people): 50%
• Lecturers:
– Prof. Ana Paiva (coordination- Alameda, some theoretical classes)
– Prof. Manuel Lopes, Dr. Pedro Sequeira (some theoretical classes
and some practical classes)
– Eng. Filipa Correia (some practical classes)
Bibliography
• “An Introduction to MultiAgent Systems” by
Michael Wooldridge, Wiley, Second Edition.
• Fundamentals of Multiagent Systems with
NetLogo Examples. José Vidal.
• Several papers distributed in the site as we
talk about them
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Practical Issues
• Project: those that want to propose a
project, need to contact us as soon as
possible.
Historial
- 1st Conference of IAD (International Workshop on Distributed Artificial
Intelligence) in the US in 1980 (after a preliminary meeting at the MIT in
1979)
- In Europe the MAAMAW happened for the first time in 1989, after the
launching of the theme in a pannel in the European Conference on Artificial
Intelligence, ECAI-88.
- The first international meeting ICMAS, happened for the first time in 1995
in the US.
- The Workshop on Agent Theories, Architectures, and Languages (ATAL) is
launched in the ECAI in 1994
- Finally the Internacional Autonomous Agents Conference (Autonomous
Agents- AA), held in 1997 a 1999 in the US, in 2000 is held in Europe.
- In 2002 the conference ICMAS and AA are merged to launch the largest
conference on agents, the AAMAS (in 2002 in Bolognha, 2003 in Austrália,
2004 in New York, 2005 in Holanda, 2006 in Japan, 2007 in The US-
Hawaii, 2008 in Portugal,2009 in Budapest and 2010 in Toronto).
Motivation
Motivation: The world today
Ubiquity
– Ubiquity – distributed computational power – mobiles, etc
Motivation: The world today
Connectivity
– Ubiquity – distributed computational power – mobiles, etc
– Connectivity – nowadays we are always connected…
Motivation: The world today
Intelligence
– Ubiquity – distributed computational power – mobiles, etc
– Connectivity – nowadays we are always connected…
– Intelligence – Tasks more and more complex to be done
by humans and computers
Motivation: The world today
Delegation
– Ubiquity – distributed computational power – mobiles, etc
– Connectivity – nowadays we are always connected…
– Intelligence – Tasks more and more complex to be done
by humans and computers
– Delegation – the need for delegating critical tasks-
example: the automatic pilot
Motivation: The world today
Autonomy
– Ubiquity – distributed computational power – mobiles, etc
– Connectivity – nowadays we are always connected…
– Intelligence – Tasks more and more complex to be done by humans and
computers
– Delegation – the need for delegating critical tasks- example: the automatic pilot
– Autonomy – more and tasks are given to machines to be performed
“autonomously” without direct control of humans;
Motivation: The world today
Serve the human
• Ubiquity – distributed
computational power – mobiles,
etc
• Connectivity – nowadays we are
always connected…
• Intelligence – Tasks more and
more complex to be done by
humans and computers
• Delegation – the need for
delegating critical tasks- example:
the automatic pilot
• Autonomy – more and tasks are
given to machines to be
performed “autonomously” without
direct control of humans;
• Serve the human– more and more
we use the human metaphors for
interaction, rather than “machine
based” one.
But what does this
means in terms of
advancements in
Computing?
....Programming...
Programming
progression…
• Programming has progressed through:
– machine code;
– assembly language;
– machine-independent programming languages;
– sub-routines;
– procedures & functions;
– abstract data types;
– objects;
to agents (relying on distribution).
Interconnection and
Distribution
Interconnection and Distribution have become core motifs in
Computer Science
But Interconnection and Distribution, coupled with the need for
systems to represent our best interests, implies systems that
can cooperate and reach agreements (or even compete) with
other systems that have different interests (much as we do
with other people)
Where does it bring us?
• Delegation and Intelligence imply the need to build computer systems
that can act effectively on our behalf
• This implies:
– The ability of computer systems to act independently and
autonomously!
– The ability of computer systems to act in a way that represents our best
interests while interacting with other humans or systems
So Computer Science
expands…
All of these trends have led to the emergence of
a new field in Computer Science:
multiagent systems and
autonomous machines
Global Computing
What techniques might be needed to deal with
systems composed of 1010 processors?
Agents and Robots in
the Rise of AI
The fourth Industrial
Revolution
The role o Agents and AI in
the rise of the 4th Industrial
Revolution
The impressive progress made in AI in recent years, driven by
exponential increases in computing power and by the
availability of vast amounts of data, has lead to the
engineering of systems that can not only to discover patterns
of behavior, make accurate predictions, but also act
“autonomously” in the world.
• Artificial intelligence is now all around us, from self-driving
cars and drones to virtual assistants and software that
predicts and invests.
AI, and Agents are behind this fourth
industrial revolution.
But what are Agents?
Agents: a definition
– “Agente é Aquele que opera”, ou “Tudo o que
age”, ou
– “Aquele que é encarregue dos negócios de
outrem”.
– There are two sides of the definition:
• An entity that is able to act
• A helper that we can delegate tasks on
Yet, authors do have different definitions of what
they mean by the term “agent”
Agents, a definition…..
Interaction with the environment: "An agent is anything that
can be viewed as perceiving its environment
though sensors and acting upon that
environment through effectors" (Russel e Norvig,
1995).
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Agents, a definition…..
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)
Agents, a definition…..
Focus on communication: "Software agents area software
components that communicate with their peers by exchanging
messages in an expressive agent communication
language" (Genesereth e Ketchpel, 1994).
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Agents, a definition…..
Focus on goals and motivations "An agent is a computational system that inhabits a
complex, dynamic environment. An agent can sense, and act on, its
environment, and has a set of goals or motivations that it tries to achieve
through these actions" (P. Maes, 1994).
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Agents, a definition…..
Focus on mobility: "Along with mobility agents have the following
computational characteristics: autonomous; asynchronous; local
interaction; parallel execution and object passing" (IBM Aglets White
paper, 1997).
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Agents, a definition…..
Focus on delegation: An agent is a program that a person or
organisation vests its authority, that can run unattended for a long time
and that can meet and interact with other agents. The person or
organisation is the agent´s authority" (White, 1994).
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Agents, a definition…..
Focus on the combination of properties: An agent is a software based
computer system that enjoys the properties of: autonomy,
social-ability, reactivity and pro-activeness" (Wooldridge &
Jennings, 1995).
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From one to many….
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Multiagent Systems, a
definition….
• A multiagent system is one that consists of a
number of agents, which interact with one-
another
• To successfully interact, they will require the
ability to cooperate, coordinate, and
negotiate with each other, much as people
do
Agent Design…. to
Society Design
The course covers two key problems:
– How do we build agents capable of independent,
autonomous action, so that they can successfully
carry out tasks we delegate to them?
– How do we build agents that are capable of
interacting (cooperating, coordinating, negotiating)
with other agents in order to successfully carry out
those delegated tasks, especially when the other
agents cannot be assumed to share the same
interests/goals?
The first problem is agent design, the second is
society design (micro/macro)
Multiagent Systems:
Questions…
• How can cooperation emerge in
societies of self-interested agents?
• What kinds of languages can
agents use to communicate?
• How can self-interested agents
recognize conflict, and how can
they (nevertheless) reach
agreement?
• How can autonomous agents
coordinate their activities so as to
cooperatively achieve goals?
Multiagent Systems
While these questions are all addressed in part by other
disciplines (notably economics and social sciences),
what makes the multiagent systems field unique is that it
emphasizes that the agents in question are
computational, information processing entities.
Multiagent Systems is
Interdisciplinary
• The field of Multiagent Systems is influenced and inspired
by many other fields:
– Economics
– Philosophy
– Game Theory
– Logic
– Ecology and Ethology
– Psychology
– Sociology
– Cognitive Science
• This can be both a strength (infusing well-founded
methodologies into the field) and a weakness (there are
many different views as to what the field is about)
• This has analogies with artificial intelligence itself
Some Views of the Field
Agents as a paradigm for software engineering:
Software engineers have derived a
progressively better understanding of the
characteristics of complexity in software. It is
now widely recognized that interaction is
probably the most important single
characteristic of complex software
Some Views of the Field
Agents as a tool for understanding
human societies
Some Views of the Field
• Multiagent Systems is primarily a search
for appropriate theoretical foundations
A vision
Welcome to the Autonomous-agents and
Multiagent Systems Course
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