Nice examples of 'negotiation' dialogues (proposal, critique, counter-proposal, explanation) in Section 2.1. Would be nicer if they can be *generated*.
Can't see how the stuff in Sections 3-5 (agent architecture etc) links to the negotiation protocol in Section 2.2.
No concept of 'assumptions' or the ability for agents to reason (make decisions/utterances) despite incomplete information. We allow for this.
No implementation, though it is claimed there is a clear link between the formal (agent architecture) model and its practical instantiation. We support our framework with an implementation.
The framework is based on an ad hoc system of argumentation. Arguments can be classified into rough classes of acceptability, but this is not enough to determine the acceptability of arguments. Also, only inconsistency *between* agents is considered; inconsistency that arises within an agent is not considered/handled. We base our framework on a general argumentation system (AABA) for which the argument acceptability semantics are clearly defined.
This is what I intend to include in the Related Work section of my forthcoming "argmas09paper":
In  a negotiation language and protocol is presented that allows for the exchange of complex proposals which can include compelling arguments for why a proposal should be adopted. Whilst  does not concentrate on the way in which arguments are built and analysed, the work is extended in  by indicating how argumentation can be used to construct proposals, create critiques, provide explanations and meta-information. However, even in , further expansion is required for agents to be able to generate and rate arguments, and for any kind of implementation to be produced. In particular, the acceptability classes used in  to rank arguments are not sufficient to resolve inconsistencies that may arise within and between agents. A more fine-grained mechanism is required. We use an existing argumentation framework (AABA) for this purpose, that is able to build and determine the acceptability of arguments, even as the knowledge bases of agents change over time (as a result of the dialogues). The AABA framework also allows agents to make assumptions, enabling agents to make decisions even despite incomplete information. Lastly, we supplement our formal model with an implementation.