Models of agents based on intentional logic

1
Models of agents based on intentional logic

• EEL 5937 Multi Agent Systems

2
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.

3
Agents as intentional systems (contd)

• The philosopher Daniel Dennett coined the term
  intentional system to describe entities whose
  behavior can be predicted by the method of
  attributing belief, desires and rational acumen.
  
• Dennett identifies different grades of
  intentional system
• A first order intentional system had beliefs and
  desires (etc.) but no beliefs and desires about
  beliefs and desires.
• A second order intentional system is more
  sophisticated it has beliefs and desires (and no
  doubt other intentional states) about beliefs and
  desires (and other intentional states) both
  those of others and its own.
• Is it legitimate or useful to attribute beliefs,
  desires, and so on, to computer systems?

4
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)

5
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.

6
So, how we design our agents?

• There are a number of intentional stances we can
  consider beliefs, desires, intentions, fears,
  wishes, preferences, , emotions love, hate,
  anger, faith.
• Which one are we going to choose?
• Various approaches were proposed.
• Cohen and Levesque beliefs and goals
• Rao and Georgeff beliefs, desires and intentions
  in a branching time framework
• Singh family of logics for representing
  intentions, beliefs, knowledge, know-how, and
  communication in a branching-time framework
• Kinny et. others BDI social plans, team work
• many others

7
Intentions

• Cohen and Levesque identify seven properties that
  must be satisfied by a reasonable theory of
  intention
• Intentions pose problems for agents, who need to
  determine ways of achieving them.
• Intentions provide a filter' for adopting other
  intentions, which must not conflict.
• Agents track the success of their intentions, and
  are inclined to try again if their attempts fail.
  
• Agents believe their intentions are possible.
• Agents do not believe they will not bring about
  their intentions.
• Under certain circumstances, agents believe they
  will bring about their intentions.
• Agents need not intend all the expected side
  effects of their intentions.

8
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.

9
Intentional notions as abstraction tools

• The intentional notions are abstraction tools,
  which provide us with a convenient and familiar
  way of describing, explaining, and predicting the
  behavior of complex systems.
• Remember most important developments in
  computing are based on new abstractions
• Procedural abstraction
• Abstract data types
• Objects.
• Agents, and intentional systems, represent a
  similar abstraction.
• So agent theorists start from the strong view of
  agents as intentional systems one whose simples
  consistent description requires the intentional
  stance.

10
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 let
  the control mechanisms figure out what to do,
  knowing that it will act in accordance with some
  built-in theory of agency (eg the Cohen-Levesque
  model of intention, or BDI logic).

11
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
  insufficiently developed tools and methodologies.

12
Practice and theory

• We will use the notions of beliefs, desires and
  intentions in our explanations and
  implementations.
• We will not strike for a conceptual purity of our
  implementation.
• We will use theoretical models as long as they
  can serve as basis for implementation.