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A Framework for Argumentation-Based Negotiation
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If we are to enable agents to handle increasingly greater levels of complexity, it is necessary to equip them with mechanisms that support greater degrees of autonomy. This is especially the case when it comes to agent-to-agent interaction which, in systems of selfish agents, often follows the format of negotiation. Within this context, a problem which has hitherto received little attention is that of identifying appropriate negotiation opponents. Furthermore, the problem is particularly difficult in dynamic systems where the need to negotiate over issues and the evaluation of resources may change over time. Such dynamics demand high degrees of autonomy from agents so that such factors can be handled at run-time and without the aid of human controllers. To that end, this paper draws inspiration from biological organisms and theories of motivation, and describes a motivation-based architecture comprising a number of motivation-based classification and selection mechanisms used to evaluate and select between negotiation opponents. Opponents are evaluated in terms of the likely issues they will want to negotiate over and the amount of conflict this might entail. Additionally, the expected cost of a negotiation with an opponent is examined in relation to the agent's current motivational evaluation of its resources. The mechanisms allow prioritisation between each method of evaluation dependent upon motivational needs. Some preliminary evaluation of the model is also presented.