Transcript Slide 1 - RMIT University

Intelligent Agents & Agent-oriented
systems
James Harland
School of Computer Science and IT
Intelligent Agents & Agent-oriented systems
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Why do we need Intelligent Systems?
• New York Stock Exchange
• 33% of shares (by volume) traded by machines
• 40% of shares (by value) traded by machines
• Needs fast response time
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Why do we need Intelligent Systems?
“The Robots are coming! The Robots are coming!”
• Mars Rover
• Home systems – vacuum, lawn mower, gutter cleaner
• Military systems --- mine clearance, sensing, weapons control, autonomous
vehicles, …
• Sensor networks
• Exoskeletons and artificial limbs
• Rescue robots
• Fish, birds, dogs, insects, …
• …
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Robots
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What is Intelligence?
talk
“Hello! How are you today. Could I please have a coffee?”
hear
Interpret “er… so.. um… as I was saying, what? No! Coffee please!”
read
Interpret “Time flies like an arrow. Fruit flies like a banana.”
think
“Low on fuel, it’s getting dark, no clue where I am … Hmmmm….”
act
Pick things up, move them, walk, build things, …
see
Distinguish moving objects from static ones, colours, textures, …
adapt
This isn’t working, so let’s try something else …
paint
Make judgements about what is pleasing and what is not
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Intelligent Systems in CS & IT
• Agent oriented programming
• Software that observes, thinks, acts and reacts
• Natural language processing and generation
• Software that can have a dialogue with humans
• Computational reasoning
• Software that can work out what to do
• Machine learning
• Software than can analyse, adapt and be trained
• Evolved Art
• Artistic collaboration with School of Media and Communication
• Interactive Toys
• Collaboration with XSiVE on toys which interact with children and grow
with them
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What is an agent?
situated: in an environment which can be sensed and acted on
pro-active: pursues its agenda, despite the environment
reactive: responds appropriately to changes in the environment
autonomous: can act on its own, without waiting to be instructed
social: can interact with other agents, and possibly humans
….
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Beliefs, Desires, Intentions
• Agents often described in terms of mental attitudes (Beliefs, Desires,
Intentions)
• Based on philosophical analysis of human reasoning by Bratman
• Developed in the early 1990s by Rao and Georgeff (in Melbourne!)
• Many variations since then
Beliefs: What it currently understands as the state of the world
Desires: States of the world that it would like to be true
Intentions: Ways of getting from current state to desired states
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‘Observe, think, act’
How does this work?
Observe
Observe
Think
Receive and process
information about
the environment
Determine which
plan should be
running
Act
Execute part of
chosen plan
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Example
Vacuum cleaner has to clean three rooms
It can move, or polish, and can sense whether a room is clean or dirty.
Observe
Beliefs:
clean(1), dirty(2), dirty(3), in(1)
Goals:
clean(1), clean(2), clean(3)
Plan:
move(1,2) then polish(2) then move(2,3) then polish(3)
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Example
Vacuum cleaner has to clean three rooms
It can move, or polish, and can sense whether a room is clean or dirty.
Observe
Beliefs:
clean(1), dirty(2), dirty(3), in(2)
Goals:
clean(2), clean(3)
Plan:
polish(2) then move(2,3) then polish(3)
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Example
Vacuum cleaner has to clean three rooms
It can move, or polish, and can sense whether a room is clean or dirty.
Observe
Beliefs:
clean(1), clean(2), dirty(3), in(2)
Goals:
clean(3)
Plan:
move(2,3) then polish(3)
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Example
Vacuum cleaner has to clean three rooms
It can move, or polish, and can sense whether a room is clean or dirty.
Observe
Beliefs:
clean(1), clean(2), dirty(3), in(2)
Goals:
clean(3)
Plan:
polish(3)
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Agents
• Applied in many contexts --- robots, finance, air traffic control,
simulations,movies,….
• Prometheus Observe
design methodology (like UML for agents)
• Agent-oriented software engineering
• Agent programming languages
• Model-checking for agents
• Reasoning about agents, beliefs, goals,…
• Agents that learn
• Bushfire simulation
• Simulation of populations
• …
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Questions?
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