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What Will Self-Aware Computer Systems Be?John Mccarthy, Stanford UniversityMccarthy@Stanford.EduHttp://Www-Formal.Stanford.Edu/Jmc/August 9, 2004

  • • Darpa Wants To Know, And There’s A Workshop T
  • • The Subject Is Ready For Basic Research.
  • • Short Term Applications May Be Feasible.
  • • Self-Awareness Is Mainly Applicable To Programs With
  • tent Existence. WHAT WILL SELF-AWARE SYSTEMS BE AWARE- • Easy aspects of state: battery level, memory available,
  • • Ongoing activities: serving users, driving a car
  • • Knowledge and lack of knowledge
  • • purposes, intentions, hopes, fears, likes, dislikes
  • • Actions it is free to choose among relative to external
  • straints. That’s where free will comes from.
  • • Permanent aspects of mental state, e.g.
  • beliefs, long term- • Episodic memory—only partial in humans, probably
  • animals, but readily available in computer systems. HUMAN SELF-AWARENESS—1- • Human self-awareness is weak but improves with age.
  • • Five year old but not three year old. I used to think- contained candy because of the cover, but now I kno
  • crayons. He will think it contans candy,
  • • Simple examples: I’m hungry, my left knee hurts from
  • my right knee feels normal, my right hand is making I
  • • Intentions:
  • Zealand some day. I do not intend to die. intend to have dinner,

    I

    intend to- • I exist in time with a past and a future. Philosophers

  • lot about what this means and how to represent it.
  • • Permanent aspects of ones mind: I speak English and
  • French and Russian. I like hamburgers and caviar. I cannot
  • my blood pressure without measuring it. HUMAN SELF-AWARENESS—2- • What are my choices? (Free will is having choices.)
  • • Habits: I know I often think of you. I often have breakfast
  • the Pennsula Creamery.
  • • Ongoing processes: I’m typing slides and also getting
  • • Juliet hoped there was enough poison in Romeo’s
  • her.
  • • More: fears, wants (sometimes simultaneous but incompatible)
  • • Permanent compared with instantaneous wants. MENTAL EVENTS (INCLUDING ACTIONS)- • choose to believe
  • • remember
  • • consider
  • • Infer
  • • decide
  • • forget
  • • realize
  • • ignore MACHINE SELF-AWARENESS- • Easy self-awareness: battery state, memory left
  • • Straightorward s-a: the program itself, the programming
  • guage specs, the machine specs.
  • • Self-simulation: Any given number of steps, can’t do
  • “Will I ever stop?”, “Will I stop in less than n steps in general—in
  • less than n steps.
  • • Its choices and their inferred consequences (free will)
  • • “I hope it won’t rain tomorrow”. Should a machine
  • be aware that it hopes? I think it should sometimes.
  • • ¬Knows(I, T T elephone(M M ike)), so I’ll have to look WHY WE NEED CONCEPTS AS OBJECTS- We had ¬Knows(I, T T elephone(M M ike)), and I’ll have
  • up.
  • Suppose T elephone(M ike) = “321-758000. If we write
  • ¬Knows(I, T elephone(M ike)), then substitution would
  • ¬Knows(I, “321-758000), which doesn’t make sense.
  • There are various proposals for getting around this.
  • advocated is some form of modal logic. My proposal is
  • individual concepts as objects, and represent them b
  • symbols, e.g. doubling the first letter.
  • There’s more about why this is a good idea in my “First
  • theories of individual concepts and propositions” WE ALSO NEED CONTEXTS AS OBJECTS- We write

    c : p

  • to assert p while in the context c. Terms also can
  • using contexts. c : e is an expression e in the context
  • The main application of contexts as objects is to assert
  • between the objects denoted by different expressions in
  • contexts. Thus we have c : Does(J oe, a) = SpecializeActor(c, J oe) : a,- or, more generally,

    SpecializesActor(c, c0, J oe) → c : Does(J oe, a)) = c- Such relations between expressions in different contexts

  • using a situation calculus theory in which the actor is
  • itly represented in an outer context in which there is
  • one actor.
  • We also need to express the relation between an external
  • in which we refer to the knowledge and awareness of
  • and AutoCar1’s internal context in which it can use “I”. SELF-AWARENESS EXPRESSED IN LOGICALFORMULAS—1
  • Pat is aware of his intention to eat dinner at home.
  • c(Awareness(P at)) : Intend(I, M M od(AAt(HHome), E
  • Awareness(P at) is a context. Eat(Dinner) denotes the
  • act of eating dinner, logically different from eating Steak
  • M od(At(Home), Eat(Dinner)) is what you get when
  • the modifier “at home” to the act of eating dinner. Intend
  • says that I intend X. The use of I is appropriate
  • context of a person’s (here Pat’s) awareness.
  • We should extend this to say that Pat will eat dinner
  • unless his intention changes. This can be expressed b
  • like ¬Ab17(P at, x, s) ∧ Intends(P at, Does(P at, x), s→ (∃s0 > s)Occurs(Does(P at, x), s).- in the notation of (McCarthy 2002).

    FORMULAS—2

  • • AutoCar1 is driving John from Office to Home. AutoCa
  • aware of this. Autocar1 becomes aware that it is low
  • gen. AutoCar1 is permanently aware that it must ask p
  • to stop for gas, so it asks for permission. Etc., Etc. These
  • are expressed in a context C0. C0 :

    Driving(I, J ohn, Home1)

    ∧Aware(DDriving(II, J J ohn, HHome)

    ∧OccursBecomes(Aware(I, LLowf uel(AAutoCar1)))∧OccursBecomes(W ant(I, SStopAt(GGasStation1)))∧

    QUESTIONS

  • • Does the lunar explorer require self-awareness? What
  • the entries in the recent DARPA contest?
  • • Do self-aware reasoning systems require dealing with
  • opacity? What about explicit contexts?
  • • Where does tracing and journaling involve self-awareness?
  • • Does an online tutoring program (for example, a program
  • teaches a student Chemistry) need to be self aware?
  • • What is the simplest self-aware system?
  • • Does self-awareness always involve self-monitoring?
  • • In what ways does self-awareness differ from awareness
  • agents? Does it require special forms of representation
  • tecture? REFERENCES
  • Some Philosophical Problems from the Standpoint of
  • Intelligence
  • John McCarthy and Patrick J. Hayes
  • Machine Intelligence 4, 1969
  • also http://www-formal.stanford.edu/jmc/mcchay69.html
  • Actions and other events in situation calculus
  • John McCarthy
  • KR2002
  • also http://www-formal.stanford.edu/jmc/sitcalc.html.