Virginia Dignum

Organizing Multiagent Systems

Despite all the research done in the last years on the development of methodologies for designing MAS, there is no methodology suitable for the specification and design of MAS in complex domains where both the agent view and the organizational view can be modeled. Current multiagent approaches either take a centralist, static approach to organizational design or take an emergent view in which agent interactions are not pre-determined, thus making it impossible to make any predictions on the behavior of the whole systems. Most of them also lack a model of the norms in the environment that should rule the (emergent) behavior of the agent society as a whole and/or the actions of individuals. In this paper, we propose a framework for modeling agent organizations, Organizational Model for Normative Institutions (OMNI), that allows the balance of global organizational requirements with the autonomy of individual agents. It specifies global goals of the system independently from those of the specific agents that populate the system. Both the norms that regulate interaction between agents, as well as the contextual meaning of those interactions are important aspects when specifying the organizational structure.

OMNI: introducing social structure, norms and ontologies into agent organizations

In this paper, we propose a framework for modelling agent organizations, Omni, that allows the balance of global organizational requirements with the autonomy of individual agents. It specifies global goals of the system independently from those of the specific agents that populate the system. Both the norms that regulate interaction between agents, as well as the contextual meaning of those interactions are important aspects when specifying the organizational structure. Omni integrates all this aspects in one framework. In order to make design of the multi-agent system manageable, we distinguish three levels of abstraction with increasing implementation detail. All dimensions of Omni have a formal logical semantics, which ensures consistency and possibility of verification of the different aspects of the system. Omni is therefore utmost suitable for the modelling of all types of MAS from open to closed environments.

Designing a Deontic Logic of Deadlines

This paper studies the logic of a dyadic modal operator for being obliged to meet a condition ρ before a condition δ becomes true. Starting from basic intuitions we arrive at a simple semantics for deadline obligations in terms of branching time models. We show that this notion of deadline obligation can be characterized in the branching time logic CTL. The defined operator obeys intuitive logic properties, like monotony w.r.t. ρ and anti-monotony w.r.t. δ, and avoids some counter-intuitive properties like agglomeration w.r.t ρ and’weak agglomeration’ w.r.t. δ. However, obligations of this type are implied by the actual achievement of ρ before the deadline. We argue that this problem is caused by the fact that we model the obligation only from the point of view of its violation conditions. We show that the property might be eliminated by considering success conditions also.

Agent-Mediated Knowledge Management

Knowledge Management (KM) is a systematic approach for sustainably improving the handling of knowledge on all levels of an organization (individual, group, organizational, and inter-organizational level) in order to support the organization’s business goals, such as innovation, quality, cost effectiveness etc. KM holistically combines activities adressing organization culture, static and dynamic organization structures, as well as ICT infrastructure (cp. [4]). ICT approaches typically fall into one of two basic system classes: One class—comprising, e.g., Organizational Memory Information Systems (OMs, cp. [1, 20])—aims at acquisition, structuring and high–precision delivery of explicit knowledge (“provide the right people with the right information at the right time”). The other class of systems—like expert finder systems or community of practice support—doesn’t rely so much on explicitly represented knowledge, but rather brings people together, for instance, to solve a given knowledge– intensive problem (see, for instance [6, 24]). Based on our practical and research experience with KM solutions, we identify the following requirements as central challenges for next generation KM systems. We can only sketch them briefly, for more detail, please refer to [38, 26]. R1: KM has to respect the distributed nature of knowledge in organizations: A KM system should therefore allow to balance between (a) global knowledge which might have or might constitute a shared context, but may also be relatively expensive; and (b) local expertise which might represent knowledge that is not easily shareable or is not worth sharing. Further, as global views cannot always be reached, a KM system must be able to handle context switches of knowledge assets, e.g., by providing explicit procedures for capturing the context during knowledge acquisition and for re-contextualizing during knowledge support. Fully accepting the ideas of distribudness means to face technical as well as organizational problems such as trust, responsibility, and contextuality. R2: KM systems must reflect the inherent goal dichotomy between business processes and KM processes.: Within an environment of bounded resources, knowledge workers will always concentrate on their first order business processes instead of KM meta processes. This means they optimize

Formal Specification of Interaction in Agent Societies

The Agent Society framework that we have developed distinguishes between the mechanisms though which the structure and global behavior of the model is described and coordinated, and the aims and behavior of the service-providers (agents) that populate the model. In this framework contracts are used to integrate the top-down specification of organizational structures with the autonomy of participating agents. In this paper we introduce LCR, a very expressive logic for describing interaction in multi-agent systems. We also show how LCR behaves in contrary-to-duty situations common to deontic logic frameworks. LCR makes it possible to check whether agents in an agent society follow some desired interaction patterns and whether desired social states are preserved by agent activity. LCR is used as a formal basis for the framework for agents societies that we are developing.

Modelling Agent Societies: Co-ordination Frameworks and Institutions

Organisations can be defined as a set of entities regulated by mechanisms of social order and created by more or less autonomous actors to achieve common goals. Multi-agent systems are a natural choice to design organisational systems due to the proactive and autonomous behaviour of agents. However, in business environments it is necessary to consider the behaviour of the global system and the collective aspects of the domain. In this paper, we argue that multi-agent systems should be designed around organisational co-ordination frameworks that reflect the coordination structures of the particular organisation. As in human societies, we argue that norms and institutions are a way for agent societies to cope with the challenge of social order. Through institutions, conventions and interaction patterns for the co-ordination of agents can be specified, monitored and managed.

Coordination, Organizations, Institutions, and Norms in Multi-Agent Systems

This book constitutes the thoroughly refereed post-proceedings of the International Workshop on Agents, Norms and Institutions for Regulated Multiagent Systems, ANIREM 2005, and the International Workshop on Organizations in Multi-Agent Systems, OOOP 2005, held in Utrecht, The Netherlands in July 2005 as an associated event of AAMAS 2005. This volume is the first in a series focussing on issues in Coordination, Organizations, Institutions and Norms (COIN) in multi-agent systems. The 17 papers in this volume are extended, revised versions of the best papers presented at the ANIREM and the OOOP workshops at AAMAS 2005 that were carefully selected during two rounds of reviewing and improvement. The papers from the two workshops have been re-grouped around the following themes: modelling, analyzing and programming organizations, modelling and analyzing institutions, modelling normative designs, as well as evaluation and regulation.

Towards Agent-Mediated Knowledge Management

In this paper, we outline the relation between Knowledge Management (KM) as an application area on the one hand, and software agents as a basic technology for supporting KM on the other. We start by presenting characteristics of KM which account for some drawbacks of today’s – typically centralized – technological approaches for KM. We argue that the basic features of agents (social ability, autonomy, re- and proactiveness) can alleviate several of these drawbacks. A classification schema for the description of agent-based KM systems is established, and a couple of example systems are depicted in terms of this schema. The paper concludes with questions which we think research in Agent-mediated Knowledge Management (AMKM) should deal with.

Towards an organizational model for agent societies using contracts

The development of multi-agent systems calls for modeling primitives that are able to represent communication, interaction, roles and other concepts that characterize multi-agent systems. Such modeling primitives are usually not provided by (single) agent languages. Furthermore, models of organizations must incorporate the collective characteristics of the domain. We propose a conceptual framework for agent societies, consisting of three interrelated models, that distinguishes between organizational and operational aspects of the domain. Contract rules specify commitments between agents and society concerning role enactment, and commitments between agents concerning interaction.

MAIA: a Framework for Developing Agent-Based Social Simulations

In this paper we introduce and motivate a conceptualization framework for agent-based social simulation, MAIA: Modelling Agent systems based on Institutional Analysis. The MAIA framework is based on Ostroms Institutional Analysis and Development framework, and provides an extensive set of modelling concepts that is rich enough to capture a large range of complex social phenomena. Developing advanced agent-based models requires substantial experience and knowledge of software development knowledge and skills. MAIA has been developed to help modellers who are unfamiliar with software development to conceptualize and implement agent-based models. It provides the foundation for a conceptualization procedure that guides modellers to adequately capture, analyse, and understand the domain of application, and helps them report explicitly on the motivations behind modelling choices. A web-based application supports conceptualization with MAIA, and outputs an XML file which is used to generate Java code for an executable simulation.