Sisteme multi-agent Universitatea

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Sisteme multi-agentUniversitatea Politehnica
din Bucurestianul universitar 2005-2006Adina
Magda Floreaadina_at_cs.pub.rohttp//turing.cs.pub
.ro/blia_06
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Curs 1

• Motivatie pentru agenti
• Definitii agenti
• Sisteme multi-agent
• Inteligenta agentilor
• Sub-domenii de cercetare

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De ce agenti?

• Sisteme complexe, pe scara larga, distribuite
• Sisteme deschise si heterogene construirea
  independenta a componentelor
• Distributia resurselor
• Distributia expertizei
• Personalizare
• Interoperabilitatea sistemelor/ integrare legacy
  systems

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Agent?

• Termenul agent este frecvent utilizat in
• Sociologie, biologie, psihologie cognitiva,
  psihologie sociala si
• Stiinta calculatoarelor ? IA
• Ce sunt agentii?
• Ce sunt agentii in stiinta calculatoarelor?
• Aduc ceva nou?
• Cum difera agentii software de alte programe?

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• Definitii ale agentilor in stiinta
  calculatoarelor
• Nu exista o definitie unanim acceptata
• De ce este greu de definit?
• IA, agenti inteligenti, sisteme multi-agent
• Aparent agentii sunt dotati cu inteligenta
• Sunt toti agentii inteligenti?
• Agent definit mai mult prin caracteristici,
  unele pot fi considerate ca manifestari ale unui
  comportament inteligent

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Definitii agenti

• Most often, when people use the term agent
  they refer to an entity that functions
  continuously and autonomously in an environment
  in which other processes take place and other
  agents exist. (Shoham, 1993)
• An agent is an entity that senses its
  environment and acts upon it (Russell, 1997)

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• Intelligent agents continuously perform three
  functions perception of dynamic conditions in
  the environment action to affect conditions in
  the environment and reasoning to interpret
  perceptions, solve problems, draw inferences, and
  determine actions. (Hayes-Roth 1995)
• Intelligent agents are software entities that
  carry out some set of operations on behalf of a
  user or another program, with some degree of
  independence or autonomy, and in so doing, employ
  some knowledge or representation of the users
  goals or desires. (the IBM Agent)

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• Agent a hardware or (more usually) a
  software-based computer system that enjoys the
  following properties
• autonomy - agents operate without the direct
  intervention of humans or others, and have some
  kind of control over their actions and internal
  state
• Flexible autonomous action
• reactivity agents perceive their environment and
  respond in a timely fashion to changes that occur
  in it
• pro-activeness agents do not simply act in
  response to their environment, they are able to
  exhibit goal-directed behaviour by taking
  initiative.
• social ability - agents interact with other
  agents (and possibly humans) via some kind of
  agent-communication language
• (Wooldridge and Jennings, 1995)

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• Caracteristici identificate
• 2 directii de definitie
• Definirea unui agent izolat
• Definirea agentilor in colectivitate ? dimensiune
  sociala ? SMA
• 2 tipuri de definitii
• Nu neaparat agenti inteligenti
• Include o comportare tipica IA ? agenti
  inteligenti

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• Caracteristici agenti
• Actioneaza pentru un utilizator sau un program
• Autonomie
• Percepe mediul si actioneaza asupra lui reactiv
• Actiuni pro-active
• goal-directed behavior vs reactive behaviour?
• Caracter social
• Functionare continua (persistent software)
• mobilitate ?
• inteligenta?
• Scopuri, rationalitate
• Rationament, luarea deciziilor cognitiv
• Invatare/adaptare
• Interactiune cu alti agenti dimensiune sociala
• Alte moduri de a realiza inteligenta?

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Mediul agentului
Proprietatile mediului - Accesibil vs
inaccesibil - Determinist vs
nondeterminist - Episodic vs non-episodic -
Static vs dinamic - Deschis vs inchis - Contine
sau nu alti agenti
Agent
Sensor intrare
Actiune iesire
Mediu
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Exemple de agenti? Agenti inteligenti?

• Thermostat
• Calendar electronic
• Lista emails
• Sistem de control al traficului aerian

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Exemple de agenti Buttler agent

• Imagine your very own mobile butler, able to
  travel with you and organise every aspect of your
  life from the meetings you have to the
  restaurants you eat in.
• The program works through mobile phones and is
  able to determine users' preferences and use the
  web to plan business and social events
• And like a real-life butler the relationship
  between phone agent and user improves as they get
  to know each other better.
• The learning algorithms will allow the butler to
  arrange meetings without the need to consult
  constantly with the user to establish their
  requirements.

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NASA agents

• NASA uses autonomous agents to handle tasks that
  appear simple but are actually quite complex. For
  example, one mission goal handled by autonomous
  agents is simply to not waste fuel. But
  accomplishing that means balancing multiple
  demands, such as staying on course and keeping
  experiments running, as well as dealing with the
  unexpected.
• NASAs Earth Observing-1 satellite, which began
  operation in 2000, was recently turned into an
  autonomous agent testbed.Image Credit NASA

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Robocup agents

• The goal of the annual RoboCup competitions,
  which have been in existence since 1997, is to
  produce a team of soccer-playing robots that can
  beat the human world champion soccer team by the
  year 2050.
• http//www.robocup.org/

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Swarms

• Intelligent Small World Autonomous Robots for
  Micro-manipulation
• A leap forward in robotics research by combining
  experts in microrobotics, in distributed and
  adaptive systems as well as in self-organising
  biological swarm systems.
• Facilitate the mass-production of microrobots,
  which can then be employed as a "real" swarm
  consisting of up to 1,000 robot clients. These
  clients will all be equipped with limited,
  pre-rational on-board intelligence.
• The swarm will consist of a huge number of
  heterogeneous robots, differing in the type of
  sensors, manipulators and computational power.
  Such a robot swarm is expected to perform a
  variety of applications, including micro
  assembly, biological, medical or cleaning tasks.

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Intelligent IT Solutions
Goal-Directed Agent technology.
AdaptivEnterprise Solution Suite allow
businesses to migrate from traditionally static,
hierarchical organizations to dynamic,
intelligent distributed organizations capable of
addressing constantly changing business demands.
Supports a large number of variables, high
variety and frequent occurrence of unpredictable
external events.
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True UAV Autonomy

• In a world first, truly autonomous, Intelligent
  Agent-controlled flight was achieved by a Codarra
  Avatar unmanned aerial vehicle (UAV).
• The flight tests were conducted in restricted
  airspace at the Australian Armys Graytown Range
  about 60 miles north of Melbourne.
• The Avatar was guided by an on-board JACK
  intelligent software agent that directed the
  aircrafts autopilot during the course of the
  mission.

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Sisteme multi-agent
Mai multi agenti intr-un mediu comun
Mediu
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Zona de influenta
Interactiuni
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SMA mai multi agenti in acelasi mediu

• Interactiuni intre agenti
• - nivel inalt
• Interactiuni pentru- coordonare
• - comunicare
• - organizare
• Coordonare
• ? motivati colectiv
• ? motivati individual
• scopuri proprii / indiferenta
• scopuri proprii / competitie pentru resurse
• scopuri proprii si contradictorii / competitie
  pentru resurse
• scopuri proprii / coalitii

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• Comunicare
• ? protocol
• ? limbaj
• - negociere
• - ontologii
• Structuri organizationale
• ? centralizate vs decentralizate
• ? ierarhie/ piata
• abordare "agent cognitiv"

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• How do agents acquire intelligence?
• Cognitive agents
• The model of human intelligence and human
  perspective of the world ? characterise an
  intelligent agent using symbolic representations
  and mentalistic notions
• knowledge - John knows humans are mortal
• beliefs - John took his umbrella because he
  believed it was going to rain
• desires, goals - John wants to possess a PhD
• intentions - John intends to work hard in order
  to have a PhD
• choices - John decided to apply for a PhD
• commitments - John will not stop working until
  getting his PhD
• obligations - John has to work to make a living
• (Shoham, 1993)

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• Premises
• Such a mentalistic or intentional view of agents
  - a kind of "folk psychology" - is not just
  another invention of computer scientists but is a
  useful paradigm for describing complex
  distributed systems.
• The complexity of such a system or the fact that
  we can not know or predict the internal structure
  of all components seems to imply that we must
  rely on animistic, intentional explanation of
  system functioning and behavior.
• Is this the only way agents can acquire
  intelligence?

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• Comparison with AI - alternate approach of
  realizing intelligence - the sub-symbolic level
  of neural networks
• An alternate model of intelligence in agent
  systems.
• Reactive agents
• Simple processing units that perceive and react
  to changes in their environment.
• Do not have a symbolic representation of the
  world and do not use complex symbolic reasoning.
• The advocates of reactive agent systems claims
  that intelligence is not a property of the active
  entity but it is distributed in the system, and
  steams as the result of the interaction between
  the many entities of the distributed structure
  and the environment.

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The wise men problem
A king wishing to know which of his three wise
men is the wisest, paints a white spot on each of
their foreheads, tells them at least one spot is
white, and asks each to determine the color of
his spot. After a while the smartest announces
that his spot is white
The problem of Prisoner's Dilemma
Outcomes for actor A (in hypothetical "points")
depending on the combination of A's action and
B's action, in the "prisoner's dilemma" game
situation. A similar scheme applies to the
outcomes for B.
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• The problem of pray and predators

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• Cognitive approach
• Detection of prey animals
• Setting up the hunting team allocation of roles
• Reorganisation of teams
• Necessity for dialogue/communication and for
  coordination
• Predator agents have goals, they appoint a leader
  that organize the distribution of work and
  coordinate actions

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• Reactive approach
• The preys emit a signal whose intensity decreases
  in proportion to distance - plays the role of
  attractor for the predators
• Hunters emit a signal which acts as a repellent
  for other hunters, so as not to find themselves
  at the same place
• Each hunter is each attracted by the pray and
  (weakly) repelled by the other hunters

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• Is intelligence the only optimal action towards a
  a goal? Only rational behaviour?
• Emotional agents
• A computable science of emotions
• Virtual actors
• Listen trough speech recognition software to
  people
• Respond, in real time, with morphing faces,
  music, text, and speech
• Emotions
• Appraisal of a situation as an event joy,
  distress
• Presumed value of a situation as an effect
  affecting another happy-for, gloating,
  resentment, jealousy, envy, sorry-for
• Appraisal of a situation as a prospective event
  hope, fear
• Appraisal of a situation as confirming or
  disconfirming an expectation satisfaction,
  relief, fears-confirmed, disappointment
• Manifest temperament control of emotions

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MAS links with other disciplines
Economic theories
Decision theory
OOP
Markets
AOP
Autonomy
Rationality
Distributed systems
Communication
MAS
Learning
Proactivity
Mobility
Cooperation
Organizations
Reactivity
Character
Artificial intelligence and DAI
Sociology
Psychology
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Areas of RD in MAS

• Agent architectures
• Knowledge representation of world, of itself, of
  the other agents
• Communication languages, protocols
• Planning task sharing, result sharing,
  distributed planning
• Coordination, distributed search
• Decision making negotiation, markets, coalition
  formation
• Learning
• Organizational theories

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Areas of RD in MAS

• Implementation
• Agent programming paradigms, languages
• Agent platforms
• Middleware, mobility, security
• Applications
• Industrial applications real-time monitoring and
  management of manufacturing and production
  process, telecommunication networks,
  transportation systems, electricity distribution
  systems, etc.
• Business process management, decision support
• eCommerce, eMarkets
• Information retrieving and filtering
• Human-computer interaction
• CAI, Web-based learning - CSCW
• PDAs - Entertainment

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