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Challenges in ABSS of Negotiation 255though it is unlikely that a wholesale change in rankings will follow from everyfailure to achieve some agreement.In order to capture this learning process about endorsements and their relativevalues, agents’ learning is represented by the Chialvo-Bak [1] algorithm.This algorithm uses a sort of neural network approach but without positivereinforcement of synapse weights. In the present case, the input neurons areattached to endorsement tokens and the output neurons are ranking values tobe attached to the endorsements. There were five intermediate layers, eachcontaining 40 neurons. Starting with the input neurons, each neuron as sevensynapses out to the next layer until the output neuron layer is reached. The pathsfollowed from input to output neurons is determined by the synapse with thehighest weight emanating from each neuron. When agreement is not reached,the value of each synapse on the dominant path is reduced by a small amount(usually by one per cent) and the sum of the reductions is distributed equallyamong the rest of the (2000+) synapses. Consequently, changes in the behaviourof an agent take place relatively infrequently but will, from time to time, be fairlyextensive.There are two advantages to be gained from implementing this learningprocess. One is that the simulations determine the most important criteria tobe used in choosing negotiating partners. The other is the flexibility of theordering of criteria since it is possible that the importance of different criteriawill change over the course of any negotiation process. It is possible, forexample, that reliability is most important at early stages so that there is somemeaningful communication but that trustworthiness is most important in thefinal stages.2.3 Negotiation strategyIt is a commonplace in the negotiation literature that the least importantissues should be addressed first. Once negotiating styles have accommodatedone another and a recognition of reliability and trustworthiness established,there is a basis for considering more important substantive issues. The mostdifficult issues are left to the last.Every agent in the model reported here adopts this sort of strategy. Eachagent offers to its preferred negotiating partner a list of positions for the issuesthe agent found least important among all of the issues that had not yet beenresolved. Denote the first agent as A and A’s preferred negotiating partner as P.If P made some offer of negotiating positions then, if that offer contained valuesfor positions that A found least important, and also some values that A foundto be more important, then A would accept P’s offer on the least importantissues in exchange for P’s acceptance of the same number of A’s positions.In general terms, some agreement could always be reached provided the two