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Do software agents know what they talk about?
Agents and Ontology
dr. Patrick De Causmaecker, Nottingham, March 7-11 2005
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
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Agents and Ontology [email protected] 4
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
Nottingham, March 2005
Agents and Ontology [email protected] 5
Mechanism-design Wanted ( Sandholm 1999):
Guarantee for succes Maximal social wellfare Pareto efficiency Individual rationality Stability Simplicity Distribution
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Auctions Pro: very simple, easy to
understand, easy to automate Pro: stimulates research for
optimal strategies Contra: too simple
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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
Nottingham, March 2005
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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?
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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
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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
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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
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Dutch auctions First-price, open cry,
descending Auctioneer starts artificially high Auctioneer lowers the price until
somebody bids First bidder wins
Winners curse…
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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.
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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.
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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.
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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…
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Negotiation Limitations of auctions:
Goods, no collaboration Only price, not value
Rosenschein en Zlotkin pioneered (1994).
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Negotiation Concepts
The negotiation set The protocol The strategies The rule of agreement
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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
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Negotiation encounters One to one Many to one Many to many
Simple Multiple
Complexity rises exponentially with the number of properties
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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.
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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()
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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.
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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.
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The negotiation set The set of reasonable deals is
Pareto optimal Individualy rational
How should an agent start?
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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.
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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
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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)
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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