Multi-player Multi-issue Negotiation with Mediator using CP-nets

Thiri Haymar Kyaw, Sujata Ghosh, Rineke Verbrugge

Abstract

This paper presents a simple interactive negotiation approach for conflicts in everyday life with incomplete information. We focus on mediation to obtain an agreement while going through alternating offers over a finite time bargaining game. The mediator searches and proposes a jointly optimal negotiation text for all players participating in the negotiation process based on their conditional preference networks (CP-nets). The players make a decision whether to accept or reject by examining their utility CP-nets. We develop two algorithms for the mediator and the players. If the first negotiation text cannot be accepted by all players, the mediator offers the next negotiation texts by searching for jointly optimal solutions. This negotiation process continues until an agreement is achieved or a deadline is reached. This proposed approach can support multi-issue, multi-party negotiation to achieve an agreement during a finite number of rounds with near optimal outcomes.

References

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  23. Algorithm 2: Negotiation by Mediator.
  24. 1: Input:
  25. 2: Player N: N = (1; 2; : : : ; n)
  26. 3: CPN1;CPN2; : : : ;CPNn //Players' CP-nets
  27. 4: S1; S2; :::; Sn //Players' proposals
  28. 5: maxP 0:9; avgP 0:5 //maximum and average acceptable probability
  29. 6: Agreement 0; JointOptimal 0/; t 0
  30. 7: threshold 0:3
  31. 8: while Agreement 6= 1 and t 6 f inalRound do
  32. 9: for i = 1 to n do
  33. 10: for j = 1 to n do
  34. 11: Search acceptableProbability (Si; S j : i 6= j)
  35. 12: end for
  36. 13: end for
  37. 14: Mark all Si; S j: acceptableProbability < threshold;
  38. 15: while maxP > avgP do
  39. 16: for i = 1 to n do
  40. 17: for j = 1 to n do
  41. 18: if 9Si : (acceptableProbability(Si; S j) = maxP ; i 6= j) then
  42. 19: JointOptimal Si
  43. 20: else
  44. 21: Search alternativeOptimal(Si) //Other proposals with same maxP
  45. 22: if 9Sl : (acceptableProbability(Sl ; S j) = maxP; l 6= j) then
  46. 23: JointOptimal Sl
  47. 24: else
  48. 25: maxP maxP 0:1
  49. 26: end if
  50. 27: end if
  51. 28: end for
  52. 29: end for
  53. 30: end while
  54. 31: Propose JointOptimal
  55. 32: if 8 Player k 2 N accept Proposal then
  56. 33: Agreement 1
  57. 34: else if Player k (k 2 N) rejects Si then
  58. 35: Ask new proposal to Player k
  59. 36: Update Si (i = k)
  60. 37: maxP 0:9
  61. 38: end if
  62. 39: end while
  63. 40: if Agreement = 0 and t = finalRound then
  64. 41: Announce finalRound and Ask for evaluating all proposals to Players
  65. 42: end if
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Paper Citation


in Harvard Style

Kyaw T., Ghosh S. and Verbrugge R. (2013). Multi-player Multi-issue Negotiation with Mediator using CP-nets . In Proceedings of the 5th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART, ISBN 978-989-8565-38-9, pages 99-108. DOI: 10.5220/0004256900990108


in Bibtex Style

@conference{icaart13,
author={Thiri Haymar Kyaw and Sujata Ghosh and Rineke Verbrugge},
title={Multi-player Multi-issue Negotiation with Mediator using CP-nets},
booktitle={Proceedings of the 5th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,},
year={2013},
pages={99-108},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004256900990108},
isbn={978-989-8565-38-9},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 5th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,
TI - Multi-player Multi-issue Negotiation with Mediator using CP-nets
SN - 978-989-8565-38-9
AU - Kyaw T.
AU - Ghosh S.
AU - Verbrugge R.
PY - 2013
SP - 99
EP - 108
DO - 10.5220/0004256900990108