Modelling Interactions via Commitments and Expectations

Organizational models often rely on two assumptions: openness and heterogeneity. This is, for instance, the case with organizations consisting of individuals whose behaviour is unpredictable, whose internal structure is unknown, and who do not necessarily share common goals, desires, or intentions. This fact has motivated the adoption of social-based approaches to modelling interaction in organizational models. The idea of social semantics is to abstract away from the agent internals and provide a social meaning to agent message exchanges. In this chapter, we present and discuss two declarative, social semantic approaches for modelling interaction. The first one takes a state-oriented perspective, and models interaction in terms of commitments. The second one adopts a rule-oriented perspective, and models interaction in terms of logical formulae expressing expectations about agent interaction. We use a simple interaction protocol taken from the e-commerce domain to present the functioning and features of the commitment- and expectation-based approaches, and to discuss various forms of reasoning and verification that they accommodate, and how organizational modelling can benefit from them.

Interactions Between Formal and Informal Organizational Networks

In this chapter we present a model of organization aimed to understand the effect of formal and informal structures on the organization’s performance. The model considers the interplay between the formal hierarchical structure and the social network connecting informally the agents emerging while the organization performs a task-set. The social network creation and evolution is endogenous, as it doesn’t include any function supposed to optimize performance. After a review of the literature, we propose a definition of performance based on the efficiency in allocating the task of a simulated organization that can be considered as a network-based problem-solving system. We analyze how the emergence of a stable process in decomposing tasks under different market conditions can alleviate the rigidity and the inefficiencies of a hierarchical structure and we compare the performance of different hierarchical structures under variable environment conditions.

Autonomous Agents Adopting Organizational Rules

This chapter discusses how autonomous agents can adopt organizational rules into their reasoning process. Agents in an organization need to coordinate their actions in order to reach the organizational goals. Organizational models specify the desired behaviour in terms of roles, relations, norms, and interactions. We have developed a method to translate norms into event-processing rules of the agents. We propose a modular reasoning model that includes the organizational rules explicitly. Since the agents are autonomous, they will have their own reasoning rules next to the organizational rules. The modular approach allows for meta-reasoning about these rules. We show that this stimulates bottom-up dynamics in the organization.

Describing Agent Societies

Agent-based approaches provide an invaluable tool for building decentralized, distributed architectures and tying together sets of disparate software tools and architectures. However, while the agents themselves have been gaining complexity, and agent specification languages have been gaining expressive power, little thought has been given to the complexity of agent societies, and languages for describing such societies. In this chapter, I propose a declarative language designed specifically for describing in an expressive way a variety of social interactions. I attempt to avoid the fallacies of artificial restriction, and similarly confounding under-specification of the design domain, yet constructing a rigorous, machine- interpretable semantics. It is my hope that introduction of such semantic will lead to a constructive dialogue between communities of agent-based social modeling and agent-based software design, and lead to a greater integration of agent development toolkits and agent-based modeling toolkits.

A Logic for Agent Organizations

Organization concepts and models are increasingly being adopted for the design and specification of multi-agent systems. Agent organizations can be seen as mechanisms of social order, created to achieve common goals for more or less autonomous agents. In order to develop a theory on the relationship between organizational structures, organizational actions, and actions of agents performing roles in the organization, we need a theoretical framework to describe and reason about organizations. The formal model presented in this chapter is sufficiently generic to enable the comparison of different existing organizational approaches to Multi-Agent Systems (MAS), while having enough descriptive power to describe realistic organizations.

Personal Assistants for Human Organizations

Intelligent software personal assistants are an active research area with the potential to revolutionize the way that human organizations operate, but there has been little research quantifying how they will impact organizational performance or how organizations will or should adapt in response. In this chapter we develop a computational model of the organization to evaluate the impact different proposed assistant abilities have on the behavior and performance of the organization. By varying the organizational structures under consideration, we can identify which abilities are most beneficial, as well as explore how organizations may adapt to best leverage the new technology. The results indicate that the most beneficial abilities for hierarchical organizations are those that improve load balancing through task allocation and failure recovery, while for horizontal organizations the most beneficial abilities are those that improve communication. The results also suggest that software personal assistant technology will facilitate more horizontal organizations.

A Framework for Dynamic Agent Organizations

This chapter presents an adaptive organizational policy for multi-agent systems called TRACE. TRACE allows a collection of multi-agent organizations to dynamically allocate tasks and resources between themselves in order to efficiently process and incoming stream of tasks. The tasks have deadlines and their arrival pattern changes over time. Hence, at any instant, some organizations could have surplus resources while others could become overloaded. In order to minimize the number of lost requests caused by an overload, the allocation of resources to organizations is changed dynamically by using ideas from microeconomics. We formally show that TRACE has the ability to adapt to load variations, reduce the number of lost requests, and allocate resources to computations on the basis of their criticality. Furthermore, although the solution generated by TRACE is not always Pareto-optimal, TRACE has the properties of feasibility and monotonicity that make it well suited to time-constrained applications. Finally, we present experimental results to demonstrate the performance of TRACE.

Structural Aspects of Organizations

In this chapter we investigate how organizations can be represented as graphs endowed with formal semantics. We distinguish different dimensions of organizations. Each of these dimensions leads to a different structure in the organizational graph. By giving the graphs a formal semantics in Description Logic we show that it is possible to formalize the effect of the organization on the activities of the agents playing the roles of the organization. Such perspective, which combines quantitative (graph-theory) and qualitative (logic) methods is shown to provide a formal ground for the study and analysis of properties of organizations which are commonly addressed only informally.

Hermes

Although intelligent agents individually exhibit a number of characteristics, including social ability, flexibility, and robustness, which make them suitable to operate in complex, dynamic, and error-prone environments, these characteristics are not exhibited in multi-agent interactions. For instance, agent interactions are often not flexible or robust. This is due to the traditional message-centric design processes, notations, and methodologies currently used. To address this issue, we have developed Hermes, a goaloriented design methodology for agent interactions which is aimed at being pragmatic for practicing software engineers. Hermes focuses on interaction goals, i.e., goals of the interaction which the agents are attempting to achieve, and results in interactions that are more flexible and robust than messagecentric approaches. In this chapter, we present the design and implementation aspects of Hermes. This includes an explanation of the Hermes design processes, notations, and design artifacts, along with a detailed description of the implementation process which provides a mapping of design artifacts to goal-plan agent platforms, such as Jadex.

Towards an Integral Approach of Organizations in Multi-Agent Systems

In this chapter, we stress the importance of thinking a MAS in all its aspects (agents, environment, interactions, organizations, and institutions), using a more integral vision. We show that a genuine organizational approach has to take into account both the environment and the institutional part of MAS societies. Then, we propose the MASQ (Multi-Agent System based on Quadrants) meta-model, which constitutes an abstraction of the various aspects of an OCMAS (Organization Centered Multi-Agent Systems), extending AGR (Agent/Group/Role). MASQ is based on a four-quadrant framework, where the analysis and design of a system is performed along two axes: an interior/exterior dimension and an individual/collective dimension. We give a conceptual definition of this approach and we will show that it is possible to apply it to practical models.