Patrizia Ribino

A Norm-Governed Holonic Multi-agent System Metamodel

Modeling and designing systems that require a high level of coordination, control and automation is a very difficult task. The problem is the lack of design processes able to cover all the features these systems present. This paper presents an extension of the ASPECS metamodel for supporting organizational and normative principles and it allows to define models not only from an holonic agent viewpoint but also from a normative organization perspective. Moreover, our work emphasizes and makes it explicit the norms that regulate the structural, behavioral and finally adaptive aspect of an organizational system. The extended metamodel was experimented creating a Virtual Enterprise model for the optimization of distributions inside the logistic districts. This organizational model is implemented using JaCaMo.

A Notation for Modeling Jason-Like BDI Agents

The design and development of a large Multi Agent System (MAS) is a complex and difficult activity where a proper modeling notation may offer a significant contribution to the formulation of the best solution. The support provided by a specific CASE tool can significantly contribute to make the chosen approach technically valid and it is also a fundamental element of a feasible development strategy. The present work reports a UML profile and the related graphical notation for describing a MAS based on the Jason meta model. Moreover a specific CASE tool has been developed for supporting MASs design and automatic code generation. The proposed notation is shown in details using a classical example from the Jason tutorial (domestic robot).

Common and domain-specific metamodel elements for problem description in simulation problems

It is well known that the multi-agent system paradigm is well suited for modelling and developing simulations of complex systems belonging to several application domains. Simulation study aims at developing simulation models useful for representing, studying and analyzing entities and their behavior in a system according to specific purposes. With our work we are trying to understand what are the right elements to be considered and included in the description of a simulation problem. In order to root our resulting metamodel in the state of the art of multi-agent simulations we started from the study of twelve papers dealing with four different application domains: Crowd Dynamics, Traffic and Transportation, Electricity Power Engineering and Supply Chain and Logistic. From this study we obtained a metamodel that may be used by an analyst as a guideline and concept repository for facing a new system design. The metamodel is the result of a well defined approach that is described together with the obtained results consisting in one core metamodel containing elements that are common to all the four application domains and some domain extension contents. These latter contain the elements that are specific of each of the studied domains and are not present in the others.

Requirement analysis abstractions for AmI system design

Current trends in the AIs evolution are going towards enriching environments with intelligence in order to support humans in their everyday life. AmI systems are plunged in the real world and humans expect to interact with them in a way that is similar to the one they have with other humans. In this kind of systems, where eliciting requirements involves several documents and stakeholders (mainly users that will be the first consumers of the system), the requirement analysis phase can be affected by incomplete, ambiguous and imprecise information. Hence, the need to find a fruitful way for knowledge management and its representation at design time. In this paper we propose a set of abstractions to be used during the early requirements analysis of AmI systems development. The result is a simple and at the same time powerful set of concepts and guidelines for providing environment knowledge representation for AmI systems.

Towards a design process for modeling MAS organizations

The design of MAS organizations is a complex activity where a proper methodological approach may offer a significant advantage in enabling the conception of the best solution. Moreover, the aid provided by a supporting tool significantly contributes to make the approach technically sound and it is a fundamental ingredient of a feasible strategy to the development of large MASs. In this paper, we introduce a portion of methodological approach devoted to design MAS organizations and a preliminary version of a specific case tool, named MoT (Moise+ Tool), for supporting activities from design production to automatic code generation. MoT provides four kinds of diagrams based on a definite graphical notation for representing organizational elements. Our process is applied to a classical write paper simulator example. Results include portion of the automatically generated code according to Moise+ specifications.

A Norm-Based Approach for Personalising Smart Environments

People have a great variety in their needs. There is a great demand for personalized services, especially those interacting with their environment. In this paper, we propose a norm based approach for personalizing smart environments that constraint user requirements by means of non functional requirements expressed in terms of permissions, obligations or prohibitions.

A heuristic for Problem Formalization in Agent Based Simulation studies

Agent Based Modeling and Simulation (ABMS) is considered an effective approach for conducting simulation studies in many fields. In order to develop high quality simulation models, methodological approaches are demanded. In such direction we are moving by proposing a heuristic for the formalization of agent based simulation problems. The proposed heuristic is based on some guidelines developed for identifying the main elements of the problem domain description by analysing verbs and their common taxonomy in grammar.

Agent-based simulation study for improving logistic warehouse performance

Logistic warehouses are critical nodes in a supply chain and improving their performance is a crucial issue when trying to avoid unproductive bottlenecks. Warehouse optimization involves several problems, some of which must be considered at the design stage and others during real-time operations. In this study, we performed an agent-based simulation to analyze the behavior of automatic logistic warehouses under the influence of specific factors, thereby obtaining indicators to supporting decision making during warehouse performance improvement. This study focused mainly on automatic warehouses where goods are moved by automatic guided vehicles.

Modeling Business Rules Compliance for Goal-Oriented Business Processes

For keeping up with competitive markets, organizations have to ensure their processes are compliant with the normative environment in which they are operating. Moreover, they must be able to adapt their processes to different normative contexts dynamically. In this paper, we propose a conceptual framework for modeling norm compliance in the context of goal-oriented systems. In particular, we provide a set of formal definitions where norms are conceived for regulating a system at a higher level of abstraction (i.e., goal level) and the norm compliance is related to the satisfiability of business process goals.

Simulation goals and metrics identification

Agent-Based Modeling and Simulation (ABMS) is a very useful means for producing high quality models during simulation studies. When ABMS is part of a methodological approach it becomes important to have a method for identifying the objectives of the simulation study in a disciplined fashion. In this work we propose a set of guidelines for properly capturing and representing the goals of the simulations and the metrics, allowing and evaluating the achievement of a simulation objective. We take inspiration from the goal-question-metric approach and with the aid of a specific problem formalization we are able to derive the right questions for relating simulation goals and metrics.