Introduction, Rules, Argumentation and Methodologies Flashcards

1
Q

When is a agent based solution fitting?

A

Agents are a metaphor for the problem, environment is appropriate (open, dynamic, uncertain), legacy software, data/control is distributed.

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2
Q

What is the goal of Agent-oriented analysis and design techniques?

A

Goal is to assist in understanding a system, to assist in designing a system

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3
Q

Abstract argument system

A

set of arguments with attack relations

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4
Q

Dung’s basic principle of argument acceptebility

A

The one who has the last word laughs the best

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5
Q

When is a set admissible?

A

If it is conflict-free and all arguments in A are acceptable with respect to A?

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6
Q

When is a set conflict free?

A

No argument in the set attack each other

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7
Q

Preferred extension

A

maximum admissible set

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8
Q

Stable extension

A

conflict free, if all agents that are not in set are attacked by the set

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9
Q

Three steps to find the grounded extension:

A

1) Green the ones not attacked or all attackers are red
2) Red the ones which are attacked by green ones
3) Go to 1 if something changed, otherwise stop

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10
Q

Ad hominem fallacy + two extensions of it

A

attack opponent instead of argument made,

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11
Q

Define argument system

A

conduct a critical discussion in which hypotheses can be constructed, tested and evaluated on the basis of reasonable arguments.

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12
Q

Define knowledge technology

A

system with expert knowledge and ability to use it

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13
Q

Define agent technology

A

individual agents that interact

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14
Q

In what do the definitions of an agent differ between Russell&Norvig Vs. Wooldridge?

A

Russel&Norvig defined an agent as anything with sensors and actuators to react.
Wooldridge: computer system capable of autonomous decisions toward goal

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15
Q

What is the difference between forward and backward chaining?

A

Backwards uses rules to go from goal to subgoals to facts, while forward goes from facts to goals.

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16
Q

What are the four characteristics of agents? Define them too

A

Reactivity (perceive and response to environment)
Proactiveness (exhibit goal-directed behaviour)
Social ability (be able to interact with other agents)
Balancing reactiveness and goal oriented behaviour (react in time to changes <=> work on (long term) goals)

17
Q

Give an example both the kind of MAS

A

SE: robots discovering maze; H&C: crops

18
Q

What are intentional systems?

A

“an intentional system is an entity ‘whose behaviour can be predicted by the method of attributing belief, desires and rational acumen’”

19
Q

Which design stances did Denett found?

A

PDI, Physical (using laws of physics to see how stuff behaves), Design (using knowledge about the purpose of the system to predict behaviour), Intentional (assigning mental stats like belief, desires and intention to the agent).

20
Q

What did McCarthy said in relation to the Intentional stance?

A

Mental qualities ascription is useful for entities where structure is unknown

21
Q

Isn’t it all just distributed/concurrent systems?

A

agents can be self-interested, so their interactions are economic, there is no global goal

22
Q

Isn’t it all just general Ai?

A

Classic Ai ignores social aspects, agent does not need very much intelligence

23
Q

Isn’t it all just economics/GT?

A

They ignored computational constraints and resource-bounded decision making

24
Q

What are the differences between agents and objects?

A

objects do something for free, agents because they want to. Agents can be social, proactive, reactive, object cannot. Also agents are multi-threaded

25
Q

Are agent just knowledge systems?

A

KS have no social ability, agents can act reactively/proactively