Download - Intelligent systems, intelligent agents
Intelligent systems, intelligent agents
New AI directions: cognitive and applications
Advantages: adaptable, flexible, able to learn, user-friendly, “bluff” intelligence
A typical agent: insurance agent (M. Minsky); many users
Other types of agents: art. life, static-mobile, distributed, for people or computers
Intelligent information society
INTELLIGENT AGENTSExamples
Internet - filtering, browsing, e-commerce, .... :
PC - system agents, OfficeHundreds of agents, more important –
agent approach = more advanced, more powerful, more modern
Definition of intelligent agent
No reasonable definition of intelligence- no theoretical definition of intelligence succeeded (empirically failed)- intelligence might be a stronger (non-computational) concept
No reasonable definition of intelligent agentsHumans capable of easily distinguishing
between (non)intelligent subjects, and between agents and non-agents
What are agents? Diverse and complex types of agents (most
important are common principles)Diverse and complex application domainsInternal structure is not essential (although
usual AI-based)Outside performance is important (like expert
systems)No reasonable definition of intelligent agentsHumans capable of distinguishing between
agents and non-agents, and the power and amount of agentness
Properties of intelligent agents
autonomy - ability to perform tasks and decisions without direct intervention of humans
social ability, ability to interact with humans and agents
responsiveness, the ability to perceive the environment and respond to changes
proactiveness, the ability to take initiative and to exhibit goal-directed behavior
adaptability, the ability of an agent to modify its behavior
mobility, the ability to change physical location
veracity, assumption of no false information
rationality, ability to perform reasonably
Properties - Pattie MaesObserves a user Gets feed-back from a user Gets direct instructions from a userGets experience from environmentAgent and user communicate, control,
executeAgent learns according to interests,
wishes and desires of users
Properties - EtzioniAutonomy when executing tasks; gets task
descriptions from a user, modifies it, performs it on its own
Time continuous – work all the time Personality - speak too much Able to communicateTo adapt to each single user – personalizationMobility
“Simple rules”does it perform typical user-oriented functions
(insurance agent)autonomy
- performs actions on its own (yes)- is prediction of actions possible (no)
adapts to each specific user- different reactions for the same error
works all the time, looks around (mobile)data - information - knowledge
Properties - summaryGeneral, not exact definitions
- “ideal agent” – theoretical, nonexistentreal agents only approximations with some properties- borders soft, not exact
Agent is a (slightly) different programSimilar relations: non/structured programming;
modular/object; information systems/operation systems/expert systems; data/information/knowledge
some people don’t understand the difference
Types of agents - Etzioni
Co-drivers – suggest where to go to Drivers – listen to suggestions by users Secretary-assistant, gets strategic
directions and performs actions on its own
LearnCooperate
Autonomous
Collaborative Learning AgentsSmart Agents
Interface AgentsCollaborative Agents
Typology of agents
Typology of agents
Types of agents
simple reflex agents condition-action, pattern-based
model-based reflex agents+ model of the world (partial)
goal-based agents + goals (desired states, boolean)
utility-based agents + utilitylearning agents + learn
Types of agents
Decision Agents Input Agents Processing Agents Spatial Agents (physical real-world)Believable agents (artif. character)Physical Agents (e.g. robot)Temporal Agents
Types of agent environments
→ More complex Observable - Partially observable Deterministic - Stochastic Episodic - Sequential Static - Dynamic Discrete - Continuous Single-agent Multiple-agent
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MAS
Multi-agent Systems (MAS)A MAS is one that consists of a number
of agents, which interact with one-anotherIn 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 interact with each other, much as people do
Can you think of an example?
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MAS
Multi-agent Systems (MAS)Autonomous software agents Local viewDecentralizationSelf-organizedOften use Knowledge Query Manipulation
Language (KQML) or FIPA's Agent Communication Language (ACL)
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MAS STUDIESagent-oriented software engineeringbeliefs, desires, and intentions (BDI)cooperation and coordinationorganisationcommunicationnegotiationdistributed problem solvingmulti-agent learningscientific communitiesdependability and fault-tolerance
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MAS FRAMEWORKS
Jade (Java)Repast (Java)Swarm (Objective-C)NetLogo (Logo)MASON (Java)SemanticAgent (SWRL) on top of JADE
Wikipedia
Bill Gates
.. computer of the future - an intelligent computer assistant, a kind of secretary, capable of communicating and executing simple mundane tasks. The new system will be capable of talking, listening, seeing, and will have other anthropological features like faces capable of expressing gestures.
(agents are the right direction)
Truly intelligent? Intelligent systems!
DEVELOPMENT, TECHNOLOGY
AI
First Slovenian agents
1993 IOI, interface VAX/VMS; B. Hribovšek, M. Gams1996 EMA, an employment agent for Slovenia on
Internet, M. Gams, A. Karalič National Employment Office
1998 Personal WebWatcher, D. Mladenič2000 ShiNa, A. Pivk2000 ActiveTools, USA, A. Bezek2007 MASDA, A. Bezek
CONCLUSION
Intelligent agents are among the most prospective new SW breeds;
Intelligent agents represents a marriage between AI, intelligent systems, and information society