Intentional Models - Multi Agent Systems - Lecture Slides, Slides of Multiagent Systems

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Models of agents based on

intentional logic

Agents as Intentional Systems

• When explaining human activity, we find it useful to

make statements such as:

• Janine took her umbrella because she believed it will rain
• Michael worked hard because he wanted a PhD.

• These statements make use of a folk psychology, by

which human behavior is predicted and explained

through the attribution of attitudes, such as believing

and wanting, and also hoping, fearing and so on.

• The attitudes employed in such folk psychological

descriptions are called the intentional notions.

Legitimacy of intentional stance

• McCarthy argued that there are occasions when the intentional stance is appropriate:
• `To ascribe beliefs , free will , intentions , consciousness , abilities , or wants to a machine is legitimate when such an ascription expresses the same information about the machine that it expresses about a person. It is useful when the ascription helps us understand the structure of the machine, its past or future behaviour, or how to repair or improve it. It is perhaps never logically required even for humans, but expressing reasonably briefly what is actually known about the state of the machine in a particular situation may require mental qualities or qualities isomorphic to them. Theories of belief, knowledge and wanting can be constructed for machines in a simpler setting than for humans, and later applied to humans. Ascription of mental qualities is most straightforward for machines of known structure such as thermostats and computer operating systems, but is most useful when applied to entities whose structure is incompletely known'. [McCarthy, 1978], (quoted in [Shoham, 1990])

What can be described by an

intentional stance?

• Turns out, almost everything can:
  • `It is perfectly coherent to treat a light switch as a (very

cooperative) agent with the capability of transmitting current at

will, who invariably transmits current when it believes that we

want it transmitted and not otherwise; flicking the switch is

simply our way of communicating our desires'. (Shoham, 1990)

• But it does not buy us anything, so it sounds ridiculous.
• Put crudely, the more we know about a system, the less we

need to rely on animistic, intentional explanations of its

behavior. However, with very complex systems, even if a

complete, accurate picture of the system's architecture and

working is available, a mechanistic, design stance

explanation of its behavior may not be practicable.

Intentions

• Cohen and Levesque identify seven properties that must be satisfied by a

reasonable theory of intention:

1. Intentions pose problems for agents, who need to determine ways of

achieving them.

2. Intentions provide a `filter' for adopting other intentions, which must not

conflict.

3. Agents track the success of their intentions, and are inclined to try again if

their attempts fail.

4. Agents believe their intentions are possible.
5. Agents do not believe they will not bring about their intentions.
6. Under certain circumstances, agents believe they will bring about their

intentions.

7. Agents need not intend all the expected side effects of their intentions.

BDI

• Belief – desire –intention model
• Belief:
  • What the agent believes about the world, as information from

different sources.

• Also, beliefs about the beliefs of other agents.
• Desire:
• The high level goals of the agent
• Intention
• Low level goals, which can be immediately transformed into

action.

• In the Rao and Georgeff formulation, these notions are

extended to reasoning in a branching time framework.

Intentional models as post-

declarative systems

• Procedural programming: we say exactly what

the system should do.

• Declarative programming: we state something

we want to achieve, give the system general

info about the relationships between objects,

and let a built-in control mechanism figure out

what to do (eg. SQL, goal-directed theorem

proving)

• Intentional models: give a very abstract

specification of the system (“desires”) and letDocsity.com

A critique of intentional models

• Intentional logic is very complicated.

• It is very difficult to program. (*)

• The resulting programming models are

computationally complex, usually

untracteable.

• There is a question if they are in fact

biologically accurate or not.

• (*) This might be just a result of the