The answers are in boldface.

  1. In FIPA-OS the core class ACL is used to contain messages. As such, it contains the methods:

  2. FIPA-OS provides a Task class. The goal in providing these is to

  3. The first things that a FIPA-OS agent must do upon startup (in order) are:

  4. In FIPA-OS a task can spawn a sub-task by

  5. The JADE threading method is such that

  6. When a JADE agent sends a message, three things are possible:

  7. JADE implements FIPA's IPs with

  8. In order to implement an agent with a GUI in JADE, you should (pick best)

  9. Which one of the following is not a software engineering method used to build better, complex software.

  10. Agent-oriented decomposition helps us implement complex systems because of all the following reasons except which one. (That is, pick the one that is not a valid reason).

  11. An agent-oriented abstraction that does not necessarily help us in implementing complex systems is:

  12. The agent-oriented philosophy for dealing with organizational relationships is appropriate for complex systems because

    The one about "boundary regions" is pure nonsense.

  13. One of the biggest problem when implementing agent systems is that

    The one about "sense of identity" is nonsense.

  14. Jennigs proposes a new "social level" which would lie where in Newell's hierarchy.

    There are no decision or interaction levels.

  15. If you use task decomposition and sharing to solve the towers of Hanoi problem with 3 disks (as explained in class), how many agents would you need?

  16. Using task decomposition and sharing we could, theoretically, solve many problems in linear time. However, this is not realistically possible for all these reasons except which one?

  17. A strong dependency in a goal graph between goals G1 and G2 represents the fact that

  18. A weak dependency in a goal graph between goals G1 and G2 represents the fact that

  19. One way we use goal graphs for building multiagent systems is:

  20. A commitment is

  21. Agent conventions

  22. A social convention

  23. The joint action convention is defined so that

  24. Goal graphs can be executed with commitments and conventions by making the obvious mappings. One of these mappings is:

  25. The filtering algorithm can do all of the things below except which one? (CSP = constraint satisfaction problem).

  26. k-consistency is defined as

  27. The hyper resolution rule

  28. The initial set of nogoods in the asynchronous backtracking algorithm is generated

  29. The main advantage of the asynchronous backtracking algorithm over the filtering algorithm is that

  30. In the asynchronous backtracking algorithm, once an agent resolves a new nogood it then

    Notice how all the wrong answers are either silly or impossible.

  31. In the asynchronous backtracking algorithm, as applied to a constraint satisfaction problem:

  32. The difference between asynchronous backtracking and asynchronous weak-commitment search is that:

  33. An advantage of asynchronous weak-commitment search over asynchronous backtracking is that:

  34. Asynchronous dynamic programming, as used to solve a path-finding problem, works by initially setting the h value of all nodes to infinity. This h value will eventually converge to h*, the shortest distance from there to the goal. Then at each step:

  35. Which one of the following statements about the asynchronous backtracking algorithm (used to solve path-finding problems) is not true.

    It does not return a path, just the distances.

  36. In the learning real-time A* algorithm (used for path-finding), what happens if the initial h(i) > h*(i)? That is, if our initial estimates overstate the truth. The LRTA* algorithm is:

    for each neighbor j
      f(j) = k(i,j) + h(j)
    h(i) = minjf(i)
    move to j with min f(j)

    Imagine that the h(goal) > 0, what happens then?

  37. Why does real-time A* use the secondmin instead of the min used by LRTA*? The LRTA* algorithm is:

    for each neighbor j
      f(j) = k(i,j) + h(j)
    h(i) = minjf(i)
    move to j with min f(j)

  38. In the moving target search problem a problem solver tries to catch a target agent. This problem can be solved using

  39. If you are solving a search problem that has n states with unidirectional search but then change to use bidirectional search, the new search space has how many states?

  40. In their efforts at cost-cutting, the University decides that all undergraduate student schedules will be generated by computer. You are given the task of implementing a system that will schedule all the classes for every incoming freshman for the next year, taking into account pre-requisites, time conflicts, etc. Which one of the algorithms below is best suited for this task?

    There is no hyper-resolution algorithm.

Copyright © 2001 José M. Vidal. All Rights Reserved.