include health institutions, electricity networks, electronic commerce, robotic systems, digital libraries, military units etc.

Problems of coordination and cooperation are not a novelty due to the birth of automated systems. They exist at multiple levels of activity in a wide range of human agents as well. People achieve their own goals through communication and cooperation with other people; and, in industrial systems, with machines as well.

The main difficulty in agent cooperation and communication is to understand each other. People and, in general, *intelligent agents* come from different organizations and individuals and thus they have different backgrounds and, maybe, different expression languages. However, natural agents get to agreements as a means for solving conflicts.

Consequently, artificial agents, in order to be reasonably similar to human agents, to an extent that grants their usefulness, are to be designed as agents that discuss to reach an agreement by starting from distinct viewpoints.

Intelligent agents have been considered in a wide number of reasons and applications, that is in all the situations in which people can delegate their interests to somebody else. In fact the word *intelligent* refers to the ability to behave, to reason and to perceive situations and the environment the agents are in like humans do. In all the applications of intelligent agents, a basic mechanism of agreement is required:
information agents, electronic commerce agents, agents in e-learning systems and legal reasoning have to know the meaning of all the information they receive from others.

In all the situations in which a misunderstanding arises, the system does not work as the user's expectations and it produces wrong outcomes.

To achieve an agreement there are fundamentally four possibilities:
- *delegate decision*: consisting in the choice of an external agent that decides for all the other agents involved;
- *judge decision*: consisting in the choice of an external agent that chooses among the proposals of the agents;
- *merging*: consisting in generating a new theory starting from the merged ones; - *negotiation*: consisting in a sequence of actions aiming at the definition of a novel, shared position, emerged from the discussion itself, by means of a group of mechanisms, established as rules of the negotiation.

In general, negotiation is a dialogue between two or more agents by which they try to reach an agreement about something starting from different viewpoints about the shared object. A negotiation process is *quantitative* when the agents discuss about how to share a set of countable objects, whereas in *Meaning Negotiation*, on which we focus in this paper, the proposals are pieces of knowledge represented by terms, i.e.

the expressions of what an agent knows about the negotiated terms. These pieces of knowledge may be accepted or rejected by the other discussants.

More specifically, Meaning Negotiation (henceforth MN) is a negotiation process in which the sharing object is the meaning of a set of terms. A common LucaWhy "acceptable"? A definition is a definition. Maybe replace with "common", "standard",...

definition of MN is: the process that takes place when the involved agents have some knowledge (some data or information) to share but do not agree on what knowledge agents share and (possibly) how they reach an agreement about it.

In this paper, we focus on the processes that take place when the agents who negotiate agree about the mechanisms to reach an agreement and disagree about the meaning of the negotiated terms. In this case, agents *know* how to reach an agreement, and see the mechanisms themselves as a protocol. We aim at designing a model of 2