Quickly locating efficient, equitable deals in automated negotiations under two-sided information uncertainty

a r t i c l e i n f o This paper develops an automated negotiation procedure inclusive of mechanism design and agent design for bilateral multi-issue negotiations under two-sided information uncertainty. The proposed negotiation mechanism comprises a protocol called MUP (Monotonic Utility-granting Protocol) and a matching strategy called WYDIWYG (What You Display Influences What You Get). The proposed preference elicitation procedure makes the agents faithful surrogates of the user they represent while the proposed Frontier Tracking Proposal Construction Algorithm (FTPCA) makes them learn the opponent's flexibility in negotiation and respond appropriately. The mechanism design and the agent design together help in locating efficient and equitable deals quickly. The efficiency, stability, simplicity, distribution symmetry and incentive compatibility of the proposed procedure are demonstrated through negotiation simulation experiments. The negotiation problem is considered complex mainly due to the indeterminacy of its outcome. For instance, any of a huge number of feasible solutions could be the outcome of a negotiation between a buyer and a seller (who have different preferences as regards to the multiple attributes — price, quality, payment terms, delivery terms etc.) of a product/service. Not all feasible solutions would be efficient. " An economic allocation or decision is efficient if and only if there is no other feasible allocation that makes some individuals better off without making other individuals worse off " [11]. Not all efficient solutions would be equitable. As noted in Ref. [25] negotiation outcomes could depend on the strategic interaction between the bargainers i.e., the better negotiator may get more utility from the derived solution than the other(s). Such solutions may not be fair to all parties involved. In economic allocations, a fair share translates to an equitable share but not necessarily an equal share. Equitable solutions in bargaining situations correspond to the Nash solution. Nash solution point is the one where the product of the corresponding individual utilities is maximized [20]. Under total information uncertainty, negotiating parties may not have much idea of the efficiency of the derived solution, but they may have some idea of its equitability based on the fairness of the derived solution. Only fair/equitable solutions would be stable in the long run. For instance, a negotiated contract that is not fair to all concerned parties would entail the risk of being reneged by the disgruntled party sooner or later. Deriving efficient and equitable deals may be straightforward when all the …