Resolving conflict and inconsistency in norm-regulated virtual organizations

Abstract

Norm-governed virtual organizations define, govern and facilitate coordinated resource sharing and problem solving in societies of agents. With an explicit account of norms, openness in virtual organizations can be achieved: new components, designed by various parties, can be seamlessly accommodated. We focus on virtual organizations realised as multi-agent systems, in which human and software agents interact to achieve individual and global goals. However, any realistic account of norms should address their dynamic nature: norms will change as agents interact with each other and their environment. Due to the changing nature of norms or due to norms stemming from different virtual organizations, there will be situations when an action is simultaneously permitted and prohibited, that is, a conflict arises. Likewise, there will be situations when an action is both obliged and prohibited, that is, an inconsistency arises. We introduce an approach, based on first-order unification, to detect and resolve such conflicts and inconsistencies. In our proposed solution, we annotate a norm with the set of values their variables should not have in order to avoid a conflict or an inconsistency with another norm. Our approach neatly accommodates the domain-dependent interrelations among actions and the indirect conflicts/inconsistencies these may cause. More generally, we can capture a useful notion of inter-agent (and inter-role) delegation of actions and norms associated to them, and use it to address conflicts/inconsistencies caused by action delegation. We illustrate our approach with an e-Science example in which agents support Grid services.

Conflict Resolution in Norm-Regulated Environments Via Unification and Constraints

“…Following [2], we base our discussion of norm conflicts on a simple representation of a virtual organisation [3] as a finite-state machine where actions of individual agents lead to state transitions. Although there are more sophisticated and expressive ways to represent agent activity and interaction (e.g., AUML [5] and electronic institutions [6], to name a few), but for the sake of generalising our approach, we shall assume any higherlevel formalism can be mapped onto a finite-state machine (possibly with some loss of expressiveness).…”

“…We regard agents adopting specific roles and, with that, a set of norms that regulate their actions within a virtual organisation. We extend our previous work [2], and introduce a more expressive norm definition, accommodating constraints. We, again, adopt the notation of [10] for specifying norms and complement it with constraints [11].…”

“…For a software agent, a machinery has to be put in place that computes a possible disambiguation of its normative situation -the set of norms Ω has to be transformed into a set Ω that does not contain any conflicting norms so that the agent can proceed with its execution. In [2], we achieved this by using a concept of curtailment -one of the norms is changed in a way so that its scope of influence is retracted from specific actions (which norm to choose for curtailment is a different matter and not discussed in this paper). By curtailing the scope of influence of a norm, the overlap between the two norms is eliminated.…”

“…Extending [2], we achieve curtailment by manipulating the constraints of the norms. In figure 3, we show how a curtailment of the prohibition changes its scope of influence and thus eliminates the overlap between the two norms.…”

“…With that, we develop further the work presented in [2] where we used first-order term unification for conflict detection and norm annotations to avoid conflicts indicating what the variables of a prohibition cannot be when actions are deployed. In this paper, we also use unification, but add constraint satisfaction for conflict detection and resolution.…”