Alternatingoffers Bargaining problems

1
Alternating-offers Bargaining problems A
Co-evolutionary Approach
Department of Computer Science
Nanlin Jin, Professor Edward Tsang, Professor
Abhinay Muthoo, Tim Gosling, Dr Maria Fasli, Dr
Sheri Markose, Guannan Wang http//cswww.essex.ac.
uk/Research/CSP/bargain

• People
• Computer Scientists
• Economists

Basic Alternating-Offers Bargaining
Problem Bargaining theory studies a class of
bargaining situations where two players have
common interests, usually called cake, but
conflict over how the cake is divided.
Under the No delay and Stationarity
assumptions, Perfect Equilibrium Partition
(P.E.P) of the basic Alternating-Offer Bargaining
is

• Technical Overview
• More Realistic Assumptions
• Co-evolutionary System
• For the bargaining problem, co-evolution is
  required as (a) the fitness is assessed by
  bargaining outcomes between strategies from
  co-evolving populations and (b) the two players
  may have different information.
• Observations
• Cake Partitions by Co-Evolution
• In general, co-evolutionary system can find out
  approximate solutions with low cost and
  reasonable time. Experimental agreements
  distribute within the P.E.P neighbourhood.

• Observations
• Co-adaptive Learning
• Strategies modify in beneficial ways to adapt to
  dynamic environments through reinforcement
  learning. Usually both players behaviours and
  bargaining outcomes stabilize near to P.E.P after
  a sufficiently long leaning period.
• Run time100 runs last for only about 1 or 2 days
• Conclusions
• Strategies do learn to perform better during
  co-evolution process.

• Players are allowed to take any division of the
  cake, if share xi ?(0, 1
• Players have neither the knowledge of P.E.P nor
  the intelligent reasoning ability as economists.
  But players have the basic common senses, that
  are the higher payoff the better, and the higher
  bargaining cost the lower payoff.
• One player doesnt know the others behaviours
  before bargaining starts
• gt bounded rationality

In Biology, co-evolution is defined as reciprocal
evolutionary change in interacting species.
Where XA and XB are the optimal share for A and
B, respectively, ?A and ?B are their discount
factors
Contact For more information, visit
Computational Finance http//cswww.essex.ac.uk/R
esearch/CSP/finance Center for Computation
Finance and Economic Agents (CCFEA)
http//www.cfea-labs.net For possible
collaboration, contact Professor Edward
Tsang Phone [phone] email
edward_at_essex.ac.ukNanlin Jin Phone 44 1206
872771 email njin_at_essex.ac.uk
Evolutionary Computation Evolution Computation,
inspired by nature, has been proved successful in
studying adaptive systems. It is especially good
for non-linear, epistatic, large search- space
problems.

• Evolution Process
• A set of candidate solutions is called a
  population
• Survival of fittest the better performance, the
  higher possibility to be selected as parents of
  the next generation
• Crossover and Mutation modifications used to
  generate the next generation.

Funding This research has been partly funded by
BT and University of Essex
In situations when we are unable to compute the
P.E.P., can we evolve sensible bargaining
strategies?