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Intelligent Agents & Agent-oriented systems James Harland School of Computer Science and IT Intelligent Agents & Agent-oriented systems.

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Presentation on theme: "Intelligent Agents & Agent-oriented systems James Harland School of Computer Science and IT Intelligent Agents & Agent-oriented systems."— Presentation transcript:

1 Intelligent Agents & Agent-oriented systems James Harland School of Computer Science and IT Intelligent Agents & Agent-oriented systems

2 RMIT University© Intelligent Agents 2

3 RMIT University© Intelligent Agents 3 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

4 RMIT University© Intelligent Agents 4 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, … …

5 RMIT University© Intelligent Agents 5 Robots

6 RMIT University© Intelligent Agents 6 What is Intelligence? talk“Hello! How are you today. Could I please have a coffee?” hearInterpret “er… so.. um… as I was saying, what? No! Coffee please!” readInterpret “Time flies like an arrow. Fruit flies like a banana.” think“Low on fuel, it’s getting dark, no clue where I am … Hmmmm….” actPick things up, move them, walk, build things, … seeDistinguish moving objects from static ones, colours, textures, … adaptThis isn’t working, so let’s try something else … paintMake judgements about what is pleasing and what is not

7 RMIT University© Intelligent Agents 7 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

8 RMIT University© Intelligent Agents 8 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 ….

9 RMIT University© Intelligent Agents 9 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

10 RMIT University© Intelligent Agents 10 ‘Observe, think, act’ How does this work? Observe Receive and process information about the environment Think Determine which plan should be running Act Execute part of chosen plan

11 RMIT University© Intelligent Agents 11 Example Vacuum cleaner has to clean three rooms It can move, or polish, and can sense whether a room is clean or dirty. 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) Observe

12 RMIT University© Intelligent Agents 12 Example Vacuum cleaner has to clean three rooms It can move, or polish, and can sense whether a room is clean or dirty. Beliefs: clean(1), dirty(2), dirty(3), in(2) Goals: clean(2), clean(3) Plan: polish(2) then move(2,3) then polish(3) Observe

13 RMIT University© Intelligent Agents 13 Example Vacuum cleaner has to clean three rooms It can move, or polish, and can sense whether a room is clean or dirty. Beliefs: clean(1), clean(2), dirty(3), in(2) Goals: clean(3) Plan: move(2,3) then polish(3) Observe

14 RMIT University© Intelligent Agents 14 Example Vacuum cleaner has to clean three rooms It can move, or polish, and can sense whether a room is clean or dirty. Beliefs: clean(1), clean(2), dirty(3), in(2) Goals: clean(3) Plan: polish(3) Observe

15 RMIT University© Intelligent Agents 15 Agents Applied in many contexts --- robots, finance, air traffic control, simulations,movies,…. Prometheus 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 … Observe

16 RMIT University© Intelligent Agents 16 Questions?


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