Do software agents know what they talk about? Agents and Ontology dr. Patrick De Causmaecker, Nottingham, March 7-11 2005.

Do software agents know what they talk about?

Agents and Ontology

dr. Patrick De Causmaecker, Nottingham, March 7-11 2005

Negotiation

Nottingham, March 2005

Agents and Ontology [email protected] 3

How can we arrive at an agreement? Sum zero games are not realistic We try to find win-win solutions There is no supervising authority We use negotiation and

argumentation



Negotiation scenario’s Mechanisms, protocols Rules of an encounter (Rosenschein,

Zlotkin 1994) Mechanism-design is the art to craft

protocols that satisfy certain conditions Once the protocol has been defined, we

look for strategies that the agents can use



Mechanism-design Wanted ( Sandholm 1999):

Guarantee for succes Maximal social wellfare Pareto efficiency Individual rationality Stability Simplicity Distribution



Auctions Pro: very simple, easy to

understand, easy to automate Pro: stimulates research for

optimal strategies Contra: too simple



Parties at an auction Auctioneer: tries to sell the goods

at the optimal price Bidders: try to buy the goods at

the optimal price, which should be below the value of their estimate



Important points Has the good a well known public

value? Has the good a well known private

value? Has the good a correlated value for

at least one of the bidders?



Dimensions How is the winner determined

Highest bidder, own price: first-price auctions Highest bidder, second price: second-price auctions

How to bid? secretly: sealed bid open: open cry

What is the bidding procedure? ascending descending one shot



English auction First-price, open cry,

ascending There is a reservation price, nobody

can go below this price Each bid must be above the previous

one. If no agent wants to bid higher, the

las bidder wins



Strategy at an English auction The dominant strategy is to bid the

minimum above the last bid until the private value is reached.

If the value of the good is uncertain The winning agent is happy: he won The winning agent is concerned: he

may have paid too much. => Winners curse



Dutch auctions First-price, open cry,

descending Auctioneer starts artificially high Auctioneer lowers the price until

somebody bids First bidder wins

Winners curse…



First price, sealed bid First-price, sealed bid

One shot Highest bidde wins

Strategy? If every agent bids its own private value, the

winner gets it at his price The delta with the second bid is what the

winner pays too much. One should bid less than one’s private value,

but more than the second’s value. No optimal strategy is known.



Vickrey auctions Second-price, sealed bid

One-shot, winner pays second price Pro: The optimal strategy is to bid the

real private value Above it, one risks to pay too much. Below does not make sense, you pay the

second price anyhow.



Vickrey auctions Display interesting properties, but

are not well understood by human bidders.

Antisocial behaviour is possible if one knows the amount that a higher bidder wants to spend on the good.



Lies and conspiracies Conspiracy is not prevented by the

protocol. Lying by the auctioneer is difficult to

prevent, especially in claused and Vickrey auctions.

Auctioneer can send someone to bid falsly…



MAFIA



Negotiation Limitations of auctions:

Goods, no collaboration Only price, not value

Rosenschein en Zlotkin pioneered (1994).



Negotiation Concepts

The negotiation set The protocol The strategies The rule of agreement



Negotiation procedure Each agent makes one proposal

per round Acording to the own strategy,

following the rules of the protocol Once agreement is reached, the

outcome is fixed Otherwise we move to the next

round



Negotiation encounters One to one Many to one Many to many

Simple Multiple

Complexity rises exponentially with the number of properties



Task negotiations A set of tasks, a set of agents and a cost

function define task negotiation <T,Ag,c>

c:(T) is monotonous: T1 T2 c(T1) c(T2)

An encounter is a sequence of sets of tasks, one assigned to each agent.



Negotiations

We discuss only one to one encounters. <T1 , T2 >, a deal is <D1 , D2 > with

D1 D2 = T1 T2

The cost for agent i of =< D1 , D2 > is costi(), the cost for a set of actions is c

(Ti). We have:

utilityi () = c (Ti) - costi()



Dominant deals

Deal 1 dominates deal 2 iff i {1,2}, utilityi( 1) utilityi (2) i {1,2}, utilityi ( 1) < utilityi (2)

A dominant deal is preferable for both partners.

A deal that is not dominated is called pareto optimal. A non pareto optimal deal can be improved for both negotiators.



Rationality The initial assignment is called the

conflict deal. It will be the result of a faulty negotiation process in which no agreement is reached.

A deal is individually rational if it weakly dominates the conflict agreement.



The negotiation set The set of reasonable deals is

Pareto optimal Individualy rational

How should an agent start?



Monotonous procedure

Protocol Both agents make a proposal Agreement rule

utility1( 1) utility1 (2) or utility2( 2) utility2 (1) Case 1 leads to 2 , case 2 leads to 1 .

If no agreement is reached, agent i is allowed to make a proposal that is worse for him.

If no agent proposes, the conflict agreement is reached.



Zeuthen strategy An agent makes the best proposal

possible. The degree of acceptability of the

conflictagreement determines who has to bid

An agent makes the minimal concession to force the opponent to bid



Risk analysis Degree of acceptability of the

conflict agreement: Riski = 0 if the present proposal is the

conflict agreement Riski = (utilityi(i)-utilityi( j))/utilityi( i)



How good is this No guarantee of succes It does end Does not maximise social wellfare Is pareto optimal Individually rational No central authority Nash equilibrium (tie resolution at random) Complex, sometimes heuristics are needed

Do software agents know what they talk about? Agents and Ontology dr. Patrick De Causmaecker, Nottingham, March 7-11 2005.

Documents

negotiation slide

simple slide

shot slide

software agents

reservation price

argumentation slide

estimate slide

optimal price bidders