Sample Exam Questions

Question 1

State and discuss the seven desirable properties of mechanism design


Convergence/guaranteed success
executing the mechanism should neccessarily result in its eventual termination, without this property negotions may continue indefinitely.
Maximising social welfare
The mechanism should lead to the best possible total outcome for all parties. (i.e. the sum of utilities of all agents should be maximal)
Pareto efficiency
A mechansim is pareto efficient if it tends to lead to outcomes where no agents benefit at the expense of other agents. An outcome is defined as pareto optimal if all outcomes would lead to a lower utility for any participant.
Individual rationality
A mechanism supports individual rationality, if it is always in the best interests of participants to comply with the protocol, that is a participant is never forced to act in such a way as to ultimatly reduce its own utility. This property should apply to the protocol as a whole, and may not apply in intermediate steps (i.e. an agent may be forced to reduce its utilit
A mechanism is stable if all participants are compelled (by their expected utility) to behave in a prescribed way, this property allows agents to model the outcomes of protocols in a predictable way. An example of stability is Nash-Equilibrium, whereby one strategy is dominant over others, such that not following that strategy will lead to a reduction in expected utility.
This property may be applied to both the design process of protocols (i.e. designers should choose simpler protocols over more complicated ones with the same behaviour) for obvious reasons. The property may also refer to the computational complexity of decisionmaking witihin the mechanism such that it is tractable for a participant to decide a strategy within the mechanism.
Mechanisms should where possible avoid depending on centralised decision making or single points of failure (i.e. a centralised arbitrator), and should take into account the capabilities of and limitations of distributed communication such as bandwidth (i.e. reducing the number of messages exchanged between participants) and communication failures.
In the event of a failure of a component (i.e. network failure) , or particpant (i.e. software crash) of the protocol the remaining participants should be able to recover, or resolve the protocol in such a way as to adversely affect the utility of any of the remaining participants.

Question 2

Describe the parameters defining English, Dutch, first-price sealed bid and Vickrey auctions and where appropriate give the dominant strategy.


First-price sealed bid

Question 3

Outline the monotonic concession protocol and the Zeuthen strategy

Question 4

Discuss the problems that arise from the use a valuation function that reduces a multi-attribute offer to a single value. Illustrate your answer with an example valuation function and appropriately chosen offers.


It is hard to differentiate between offers based on multiple criteria. For example, if the valuation function is f(x,y) = 0.2x+0.8y and there are two offers (1,1) = 1 and (2,0.75) = 1, they cannot be differentiated.

Question 5

State and justify The four properties of institutions that provide a basis for trust and security in agent interaction.


decrease uncertainty
because purpose of the institution is to enable a particular kind of interaction, the probability is increased that only agents with co-incident goals will enter the institution
reduce conflict of meaning
the domain of discourse is largely pre-determined by the shared institutional goals, so that alternative meanings are largely precluded.
create expectations of outcome
the purpose of interacting within an institutional framework is because of a desire to achive a certain goal or set of goals, hence objective is shared
simplify the decision process
the possibility space is pruned through the restricted domain and through the shared goal(s), so there are fewer options to consider.

Question 6

Name and describe the four classes of norm as they occur in agent-based systems.


vague desires, possibly contradictory, probably unenforceable
abstract norms grounded in ontology, open to reasoning
concrete specifications of (un)acceptable actions, and obligations, declarative style
concrete specifications of sequences of actions, options, outcomes

Question 7

Consider the institutional framework of the lecture:
  1. Identify some roles, scenes, and conversations (precise formal specifications are {\em not} required), but you may use diagrams to illustrate your answers.
  2. Propose an abstract norm, a concrete norm and a rule that might govern behaviour in a lecture.


  1. Although this situation was used as illustration in a lecture, this part of the question is primarily aimed at getting students to apply knowledge in a new (ish) situation.

    Roles: teacher, learner, collaborator

    Scenes: presentation, discussion, question, group-working

    Conversations: a simple protocol situated in one of the above scenes and illustrating a possible interaction

  2. abstract: treat others with respect, as you would wish to be treated yourself; learning is useful

    concrete: listen while others are speaking; don't put other people down; engage in the topic being taught; ask relevant questions; rule: if you want to ask a question, raise your hand; if your mobile rings then switch it off;

Question 8

Speech acts typically have two components: name them and then list five different kinds of speech acts along with illustrative examples.


A speech act consists of a performative which indicates the intention of the speech act and a proposition.

kinds are:

inform the recipient
get recipient to do something
commit speaker to do something
speaker expresses mental state
speaker announces something

Question 9

Negotiation strategy can be characterized by the initial offer an agent makes and the way in which an agent changes its reaction to offers over time. Describe in detail the key aspects of the {\em monotonic concession} and the {\em Zeuthen} strategies.

Question 10

Contract net is a very structured form of negotiation used to achieve task sharing. Outline the five phases of the contract net protocol and what problems may arise in practice.


  1. Problem recognition: an agent (initiator) identifies a task that it is unable to fulfill (and a set of agent who may be able to fulfill the task)
  2. Task Announcment: initiator broadcasts a "Call For Proposals" message to potential actors. This message contains a description of the problem.
  3. Task Analysis/Bidding: participants analyse the task and determine if they are capable and willing to perform the task, if they are they send a "Bid" describing their capabilities which are relevant to the task and under what terms they are willing to fulfill the request.
  4. Contacting: The initiator selects a bid from the set received based on its own preferences, and allocates the contract to the winning bidder (simultaneously notifying other bidders of their failure to contract). If no bids are received the protocol ends.
  5. Task Completion: Once the winning bidder receives its winning notification it performs the task and notifies the initiator when it is complete

Example problems include: task specificaiton, QoS, choosing between competing offers, differentiating between offers based on multiple criteria.

Question 11

A grass-cutting robot can perceive the presence of grass or null (meaning just something else) and has the following repertoire of actions:

The goal of this robot is to wander around the garden, which comprises grassed areas and paths, cutting grass whereever it finds it. To specify the agent behaviour, you may use the following three domain predicates:

Now answer the following questions:

  1. Draw a diagram of the garden in which the robot is going to operate and then Write down and explain the rules you would use
    1. to control cutting
    2. to control movement

    You may assume the garden is rectangular with the farthest corner at (maxx, maxy).

  2. Discuss how you would extend the rule set, percepts, actions and/or predicates to prevent the robot from moving on to flower borders.
  3. Do you feel this is an appropriate architecture for the task or would a subsumption architecture be more suitable? Consider how Steel's Mars explorer model might be adapted for this environment. Statement of rules is not required.


  1. In(x,y) & Grass(x,y) -> Do(cut)
    In(0,0) & Facing(north) & not(Grass(0,0)) -> Do(forward)
    In(0,0) & Facing(south) & not(Grass(0,0)) -> Do(turn)
    In(0,0) & Facing(east) & not(Grass(0,0)) -> Do(forward)
    In(0,0) & Facing(west) & not(Grass(0,0)) -> Do(turn)
    and similarly but differently for other corners
    In(0,x) & Facing(west) & not(Grass(0,x)) -> Do(turn)
    In(0,x) & Facing(d) & not(Grass(0,x)) -> Do(forward)
    and similarly but differently for the other boundaries
  2. Looking for general evidence of thinking. Hope no one proposes hard-coding the border edges in the same way as the limits of the garden. Simplest solution is probably to arithmetic in the Grass predicate: In(x,y) & Facing(north) & not(Grass(x,y+1)) -> Do(turn) and similarly but differently for facing other directions. Other solutions might involve introducing a new percept earth and perhaps a new predicate Look. Good student might also remark upon the problem of ordering the rules to get the right results and how this gets increasingly difficult as the size of the ruleset increases
  3. More evidence of thinking required. Could posit the existence of a radio transmitter in the centre of the garden (doesn't have to be exactly in the centre tho, or really even anywhere near the centre!), then robot can use the gradient effect for navigation (and depositing the grass clippings, so best put the transmitter in the compost heap). The radio-active crumbs should be used now not to reinforce a particular path, but instead to make a robot go in a different direction.

Question 12

Name and characterise the commonly agreed properties of an agent.


Key properties (agents may assume a subset of these):
This is the key property differentiating agents from say objects, agents should have the capacity to decide for themselves whether or not to take a given action. Agents may be proative (Taking action without explicit external stimulous) and/or reactive (only taking action based on external events) in both cases there is a causal decoupling between elements or events in the environment and the agents actions (i.e. the agent is in some way responsible for its own actions).
Situated in an Environment
Agents are assumed to have some external environment with which they interact. This may be the phisical world, a software simulation or a set of other agents or some other system. The key is that there are things outside the agent which it interacts with that it does not have immediate control over.
Communicative (Also Social Ability)
In the field of software agents a key property is typically the ability of an agent to communicate and exchange instructions and information with other agents.
Other valid properties which may apply to some but not all agents:
The ability for an agent to move between (sub) environemnts on different machines at different physical localtions
It is often common to assume that agents do not give out information which they know to be false
Agents decisions may be supported by a sound reasoning
Agents may adapt and changee to deal with changes in their environment

Question 13

Constrast the costs and benefits of algorithmic, declarative and utility-driven approaches to programming an agent.



Question 14

Outline the subsumption architecture and explain its strengths and weaknesses


Question 15

Describe the key characteristics of Steels's Martian explorer subsumption architecture and explain how it worked.


Question 16

Explain how utility functions were used in the TileWorld.


Tileworld consists of a two dimensional grid, each cell in the grid may contain nothing, a tile, a hole or an obstacle. An agent is placed on an empty cell of the grid, where it may move up, down, left or right. It may not move into cells containing holes or obstacles, agents may move into cells containing tiles, if the cell beyond the block in the direction of movement does not contain an obstacle. If the cell beyond the tile contains a hole then the hole is filled by the tile, and becomes empty. Depending on the paramaters of the experiment, tiles, holes and obstacles may appear with given probabilites at a given time, and my dissapear at a later time. The experiment is run by placing the agent at a point determinied by the experimentor (or at random) and running the envirnment for a given number of steps.

The utility of a an agent's run (i.e. over the duration of the experiment) is defined as a function as follows:

            number of holes filled in r
 u(r) = ----------------------------------
         number of hoes that appeared in r
The utility over a run is used to determine an agents performance in that run, where a utility of 0 indicates that the agent failed to fill any holes, and 1 indicates that the agent filled all holes.

An optimal agent in tileworld is defined as one which maximises its expected utility over all possible runs. That is in any given environment, the anent always makes decisions which are most likely to lead to the maximum utility. An example might be abandoning the decision to move toward a distant tile, in favour of a nearer one which is less likely to dissapear by the time the agent gets there, or moving to distant regions with more tiles and holes instead of trying to fill local holes will fewer tiles.

Question 17

Explain the purpose of agent communication languages and agent content languages, explaining why both are necessary and giving examples of each.


Agent communication languages are 'outer' languages which are intended to express the general semantics, force and purpose of a mesasge, they typically also indicate the sender and intended receiver (and/or actor to which the message applies), and other properties of the message. Communication languages are typically build based on Searle's Speech-act theory, using a fixed set of Performatives, which characterise a mesage into one of a set of commonly identified interaction types, performatives are common to all agents using a given commnucation language. Additonally mesages contain some content expressed in a Content Language which is given meaning by the enclosing performative. Examples include KQML and the FIPA ACL.

Content languages are used to express properties and queries in a given domain to which the message is relevant. Content languages are typically domain dependant, their structure and semantics are defined by an ontology. Examples of content languages are KIF and FIPA-SL.

Question 18

Why is Vickrey's protocol effective and what are its advantages? In what circumstances is its use not advisable?

Question 19

Describe the BDI architecture (define the acronym BDI first) and how this is realised in the PRS system.


BDI stands for "Belief Desire Intention" and applies to a mechanism for modeling agents 'mental states', Beliefs correspond to things which the agent knows to be true at the curren time, Desires to the agents overall goals (goals which should be maintained until they are acheived or can never be acheived) , and Intentions to the agents immediate planned actions. Within PRS a set of fixed plans are defined which indicate a (possibly structured) sequence qof actions (which may be conditional on certain beliefs (pre-conditions)) and their post-conditions. The agent is given one or more goals to acheive, the first of these is pushed onto the intention stack. The agent then searches for a plan or sequence of plans which should result in the goal being acheived (delibuand pushes these onto the intention stack untill a plan whos pre-conditions match the current beliefs is found. The actions specified by the top plan are executed until either the plan is acheived or the beliefs of the agent no longer met by the preconditions of the top plan on the intentions stack, in which case a new plan is calculated.

Question 20

How might a plan library be of use and be used by an agent?


Typically planning agents do not build plans from scratch, isntead a plan library is used, consisting of a pre-defined set of plans. Each plan in the library is typically expressed in terms of a set of pre-condidions must be satisfied for the plan to be implemented, a set of actions and a set of post-conditions which will (probably) be satisfied when the actions are executed.

Plan selection within an agent can be done by running though the plans and find those who's post-conditions unify with one or more of the agents intentions, and whos pre-conditions unify with the agent's current beliefs.

Question 21

Sketch the prototypical structure of a negotiation protocol.

Question 22

Sketch the structure of a deductive reasoning agent, illustrate with an example and discuss the limitations of the logic-based approach.

Question 23

In what situations might mobile agents be appropriate technology, what are the major technical issues created by them and how might they be resolved.

Question 24

Why is modal logic an excellent logic for modelling multi-agent systems?

Question 25

Explain action selection when you consider an agent as a theorem prover

Question 26

Consider the following situation: We have a small robotic theorem proving agents that needs to find an objectin in a room (a grid of 3x3) with obstacles. Your agent is only capable of moving forward, turning 90 degress clockwise, and picking up the object.
  1. What are the domain predicates
  2. What are the actions of your agent
  3. Provide an initial environment
  4. Provide the rules necesarry for your agent to accomplish its goal (finding the object) in your initial environment. Make sure that this includes at least 5 rules and involves all of the possible actions your agent can perform. Make sure that your rules are written in a general form that would allow them to be used with other initial environments.

Question 27

Describe means-end reasoning.

Question 28

What are hybrid systems? Elaborate on the various types of layering.

Question 29

Find the Nash equillibria of the following games:
  1. C D
  2. D E F
  3. C D

Question 30

Remove the dominated strategies from the following games. Show each step.
  1. D E F
  2. E F G H

Question 31

  1. What are the nash equillibria for the following extensive game with perfect information:
                     /    |    \
                   /      |      \
                 /        |        \
          (2,1)/     (1,1)|     (0,2)\
             /            |            \
           2              2              2
         /   \          /   \          /   \
        y1    n1       y2    n2       y3    n3
       /       \      /       \      /       \
      2,0      0,0   1,1      0,0   0,2      0,0   
  2. Give an example of a game that produces unintuitive Nash equilibria. Explain Why.
  3. Explain backward induction in the context of equilibria for extensive games with perfect information

Question 32

Explain how model logic extends classical logic. Give both syntax and semantics.

Question 33

How can modal logic be interpreted as an epistemic logic for multi-agent systems?

Question 34