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GOLOG David Mui EEL6938

GOLOG David Mui EEL6938 . Outline. Introduction Situational Calculus GOLOG Personal Banking Assistant Using GOLOG ConGOLOG – GOLOG variant Conclusion. Introduction. Computers System Embedded in complex environments

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GOLOG David Mui EEL6938

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  1. GOLOG David Mui EEL6938

  2. Outline • Introduction • Situational Calculus • GOLOG • Personal Banking Assistant Using GOLOG • ConGOLOG – GOLOG variant • Conclusion

  3. Introduction • Computers System • Embedded in complex environments • Software for such systems does not maintain explicit model of the world • Users and designers of the system have a general mental model of the environment • Designers/Programmers • Problematic because they need to reconstruct the model • Difficult to extend because of high level abstraction • Solution: GOLOG

  4. GOLOG • What is GOLOG? • Logic Programming Language for Dynamic Domains • Maintains explicit model of environment domain • Can be queried, reasoned at runtime • Based on theory of actions and preconditions • An Extension of situational calculus • First,Second order logic • Applications of GOLOG? • Robotics • Artificial Intelligence • Mechanical Devices • Modeling and Simulation

  5. Situational Calculus • Logic Formalism designed for representing dynamic domains • First Order/Second Order logic formulae • Actions performed in the world • Fluent describe the world state • Can be thought of as properties of the world • Situations • Finite sequence of actions • Changes to the environment result in Actions. • Actions can be parametrized • Sequence of actions is described as a situation • S0 defined as initial situation constant (no action or situation)

  6. Situational Calculus Cont. • Binary function do: • do(a,s), denotes successor situation based on “a” (action) on “s” (situation), (i.e. the new situation) • Example: • pickup(A ,S0) • do(putdown(A) ,do(walk(L), do(pickup(A) ,S0)))

  7. Situational Calculus Cont. • Properties of the environment or world can be seen as fluents • Relational Fluents • Truth values that may change • is_carrying(robot, item, s) • Functional Fluents • Functions that take the situation as their final argument • Returns a situation dependent value • loc(robot, s)

  8. Creating Axioms from Actions • Actions and effects of the actions are axiomatized • Actions have preconditions. • World Dynamics are specified by effect axioms

  9. Frame Problem • To define a dynamic world it requires more than just action preconditions and effect axioms • Frame Axioms • Defines action invariants of the domain • Could be a vast number of frame axiom in a domain • Fluents unaffected by the action • Example: • If robot picks up an object location does not change.

  10. Solution to the Frame Problem • Generate Successor state Axiom • Collect all effect axioms from fluent and make a completeness assumption • Assume it specifies all possibilities the fluent may change • Transform effect axioms to generate successor state axiom of given fluent

  11. Situational Calculus, Cont. • A domain is defined by the following theory: • Axioms defining the world in different situations • Action preconditions • Successor state axioms • Foundational axioms

  12. Complex Actions in GOLOG • Situational Calculus methods described in previous slides can not handle complex actions and reasoning • Procedures • Loops • Nondeterministic actions • Need to define complex actions with additional symbols

  13. Complex Actions, cont. • Define Complex Actions using extralogical symbols (e.g., while, if, etc.) • Extralogical expressions are macros that expand into formulas • Do(δ, s, s`) is the basic abbreviation in the GOLOG language, where δ is a complex action expression, for complex operations • Do(δ, s, s`) means that executing δ (complex action) in situation “s” has s` as a terminating situation

  14. Complex Actions, cont. Complex Actions, cont. Complex Actions, cont. Complex Actions, cont. 1.Primitive Actions 2. Test Actions 3. Sequence

  15. Complex Actions, cont. 4. Nondeterministic choice of two actions 5. Nondeterministic choice of two arguments 6. Nondeterministic Iterations

  16. Complex Actions, cont. • Conditional and loops definition in GOLOG • Procedures difficult to define in GOLOG • No easy way of macro expansion on recursive procedure calls to itself

  17. Complex Actions, cont. • Create auxiliary macro definition: For any predicate symbol P of arity n+2 taking a pair of situation arguments • Define a semantic for procedures utilizing recursive calls

  18. GOLOG in a Nutshell • GOLOG programs are executed uses a theorem prover • User supplies, axioms, successor state axioms, initial situation condition of domain, and GOLOG program describing agent behaviour • Execution of program gives:

  19. Example GOLOG • Elevator Controller Example • Primitive Actions • Up(n): move the elevator to a floor n • Down(n): move the elevator down to a floor n • Turnoff: turn off call button n • Open: open elevator door • Close: close the elevator door • Fluents • CurrentFloor(s) = n, in situation s, the elevator is at floor n • On(n,s), in situation s call button n is on • NextFloor(n,s) = in situation s the next floor (n)

  20. Example, cont. • Primitive Action Preconditions • Successor State Axiom

  21. Example, cont. • One of the possible fluents • Elevator GOLOG Procedures

  22. Example, cont. • Theorem proving task • Successful Execution of GOLOG program • Returns the following to elevator hardware control system

  23. Personal Banking Assistant Using GOLOG • Personal Banking Assistant (PBA) • Assists users in personal banking over computer networks • Perform transactions based on certain actions, preconditions, and situations • Collection of GOLOG agents that interact • Over 2000 lines of GOLOG Code • Currently implemented in simulated financial environment

  24. System Components • Personal Banking Assistant Agents • User interface, performs actions directed by user, and monitors for certain situations • Bank Agents • Perform backend bank operations on accounts • Transfer Facilitator Agents • Conducts fund transfers between different bank institutions • Router Agents • Performs network operations/maintenance • Automated Teller Agents • Provides ATM interface to bank agents

  25. System Diagram

  26. PBA Fluents • Fluents used by the PBA to model the world: • USERACCOUNT(type, bank, account, balance, lastUpdate, rateOfReturn, moveFunds, minBalance, penalty, refreshRate, s) • Monitor(type, bank, account, limit, lowerOrHigher, priority, response, monID, s) • ALERT(alertMessage, maxPriority, monID, s) • ALERTACKNOLWEDGED(monID,s) • WAITINGUPDATE(bank, account, s)

  27. PBA Primitive Actions • SENDMESSAGE(method, recipient, message) • STARTWAITINGUPDT(bank, account) • STOPWAITINGUPDT(bank,account) • CREATEALERT(message, maxPriority, monID) • SENDALERT(priority, message, medium, monID)

  28. PBA, cont. • ControlPBA • Requests balance updates for accounts • Process messages • Send out alert messages to users

  29. PBA, cont. • RefreshMonitoredAccts • Request balance updates for accounts • Process new messages • Send out new messages to users

  30. PBA, cont. • HandleCommunications Procedure • Main message handling loop • Reads message from port and dispatches to appropriate action • GenerateAlerts Procedure • Directs agent to monitor triggers defined by user • Alerts the user

  31. PBA Results • Pros: • GOLOG capable of building useful applications • Provides structure for the programmer • Preconditions, successor state axioms • Encourages a layered design • Cons: • Certain operations are tricky to accomplish • Performing arithmetic • Assigning a value to a variable • Limited debugging tools • Lack of standard libraries • Lack of event driven reactive behaviors

  32. ConGOLOG

  33. ConGOLOG • Extended version of GOLOG that incorporates concurrency • Concurrent processes with different priorities • High level interrupts • Arbitrary actions • ConGolog differs from other formal models of concurrency • Allows incomplete information about the environment • Allows primitive actions to affect the environment in a complex way and such changes to the environment can affect the execution of the remainder of the program

  34. New Semantic for Concurrency • ConGOLOG adopts a transition semantic • Trans Predicate • Defines a transition relation between two processes • Final Predicate • Final process • Determines when process is completed

  35. Trans Axioms 1. Empty Program 2. Primitive Action 3. Wait/Test Actions

  36. New Concurrency Constructs • Constructs to handle concurrent programming in ConGOLOG

  37. Other GOLOG Variants • CcGOLOG • Incorporates continous change and event driven behavior • GOLEX • Execution and monitoring system, distributed control software • Autonomous mobile robots, sensing and interaction • IndiGOLOG • Incremental Interpreter for high level programs involving nondeterminisim and sensing actions

  38. Conclusion • Logic programming for dynamic domains such as robotics, intelligent software agents, and modeling and simulations • GOLOG is based on situational calculus, utilizing first/second order logic and formal theory of actions • Variants (ccGOLOG, ConGOLOG…etc.) • To solve weakness such as concurrency, event driven, sensing

  39. References • Hector J. Levesque, Raymond Reiter, Yves Lesperance, Fngzhen Lin, and Richard B. Scherl. GOLOG: A logic programming language for dynamic domains. To appear in the Journal of Logic Programming, special issue on Reasoning about Action and Change, 1996. • Yves Lesperance, Hector J. Levesque, and Shane J. Ruman. An Experiment in Using GOLOG to Build a Personal Banking Assistant. To Appear in Intelligent Agent Systems: Theoretical and Practical Issues, 1997.

  40. References, cont. • Giuseppe De Giacomo, Yves Lespérance, and Hector Levesque. ConGolog, a concurrent programming language based on the situation calculus. Artificial Intelligence, 121(1-2):109-169, 2000. • Yves Lespérance, Todd G. Kelly, John Mylopoulos, and Eric S.K. Yu. Modeling dynamic domains with ConGolog. In Proceedings of CAiSE-99, Heidelberg, Germany, June 1999.

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