International Journal of Cooperative Information Systems

Numerous works aim to design agents and multi-agent systems architectures in order to enable cooperation and coordination between agents. Most of them use organizational structures or societies metaphor to define the MAS architecture. It seems improbable that a rigid unscalable organization could handle a real world problem, so it is interesting to provide agents with abilities to self-organize according to problem's objectives and environment dynamics. We have chosen the holonic paradigm to provide these abilities to agents. Holons are recursive self-similar entities which are organized in an emergent society — an holarchy. The aim of this paper is to present a formally specified framework for holonic MAS which allows agents to self-organize. The framework is illustrated by an example drawn from a real world problem. Some pertinent properties concerning the self-organizing capabilities of this framework are then proved.

To analyze emergent behavior, a formal framework is needed to characterize the structure and dynamics of complex interaction-based multi-agent systems. We introduce an extension of an existing agent testbed for artificial societies making it possible to formally analyze the dynamics of the simulated agent system. The extension generates temporally annotated logical terms that describe parts of the dynamics of the simulated system. Based on these terms, it is possible to validate hypotheses about the system on different levels of aggregation, i.e. agent, group and system level. We present first results from a set of simple experiments in a class of artificial societies.

In this work, we present a simulation study drawn upon a famous ethological example: food-sharing habit of vampire bats in Central America. A norm of reciprocity is introduced when agents are expected to exhibit a cooperative behavior under serious environmental strictures (infrequent but lethal food scarcity). We compare different agents' architectures (with different levels of cognitive complexity) in the evolution of food-sharing habit and we analyze their performances against the presence of cheaters in the population. The experiments are aimed at studying the role of cognitive mediators (i.e. goals) in spreading altruism, described as a purposeful action.

Norms and institutions have been proposed to regulate multi-agent interactions. However, agents are intrinsically autonomous, and may thus decide whether to comply with norms. On the other hand, besides institutional norms, agents may adopt new norms by establishing commitments with other agents. In this paper, we address these issues by considering an electronic institution that monitors the compliance to norms in an evolving normative framework: norms are used both to regulate an existing environment and to define contracts that make agents' commitments explicit. In particular, we consider the creation of virtual organizations in which agents commit to certain cooperation efforts regulated by appropriate norms. The supervision of norm fulfillment is based on the notion of institutional reality, which is constructed by assigning powers to agents enacting institutional roles. Constitutive rules make a connection between the illocutions of those agents and institutional facts, certifying the occurrence of associated external transactions. Contract specification is based on conditional prescription of obligations. Contract monitoring relies on rules for detecting the fulfillment and violation of those obligations. The implementation of our normative institutional environment is supported by a rule-based inference engine.

Normative multiagent systems provide agents with abilities to autonomously devise societies and organizations coordinating their behavior via social norms and laws. In this paper, we study how agents negotiate new social norms and when they accept them. We introduce a negotiation model based on what we call the social delegation cycle, which explains the negotiation of new social norms from agent desires in three steps. First, individual agents or their representatives negotiate social goals, then a social goal is negotiated in a social norm, and finally the social norm is accepted by the agents when it leads to fulfillment of the desires the cycle started with. We characterize the allowed proposals during social goal negotiation as mergers of the individual agent desires, and we characterize the allowed proposals during norm negotiation as both joint plans to achieve the social goal (obligations associated with the norm) and the associated sanctions or rewards (a control system associated with the norm). The norm is accepted when the norm is stable in the sense that agents will act according to the norm, and effective in the sense that fulfillment of the norm leads to achievement of the agents' desires. We also compare norm negotiation with contract negotiation and negotiation of the distribution of obligations.

The decoupled nature of computing in mobile ad hoc networks (MANETs) can result in disconnections at inopportune times during an interaction between a pair of hosts. We introduce the notion of a priori selection of partner hosts to reduce the likelihood of disconnection during such interactions. An application may specify the times when and the physical locations where it requires interactions with peer applications on partner hosts. A knowledge base of the physical motion profiles of various hosts maintained on each mobile host is used to select partner hosts that are co-located with the reference host at the required time and are least likely to disconnect. In this paper, we present a formal model for such knowledge management, along with an algorithm used to determine suitable partner hosts. We also provide details of our implementation of partner selection, which has been used in the context of a service-oriented computing middleware for MANETs, developed previously by our group. Finally, we present simulation results of our approach.