Michele Piunti

Environment programming in multi-agent systems: an artifact-based perspective

This article introduces the notion of environment programming in software multi-agent systems (MAS) and describes a concrete computational and programming model based on the artifact abstraction and implemented by the CArtAgO framework. Environment programming accounts for conceiving the computational environment where agents are situated as a first-class abstraction for programming MAS, namely a part of the system that can be designed and programmed—aside to agents—to encapsulate functionalities that will be exploited by agents at runtime. From a programming and software engineering perspective, this is meant to improve the modularity, extensibility and reusability of the MAS as a software system. By adopting the A&A meta-model, we consider environments populated by a dynamic set of computational entities called artifacts, collected in workspaces. From the agent viewpoint, artifacts are first-class entities of their environment, representing resources and tools that they can dynamically instantiate, share and use to support individual and collective activities. From the MAS programmer viewpoint, artifacts are a first-class abstraction to shape and program functional environments that agents will exploit at runtime, including functionalities that concern agent interaction, coordination, organisation, and the interaction with the external environment. The article includes a description of the main concepts concerning artifact-based environments and related CArtAgO technology, as well as an overview of their application in MAS programming.

Environment Programming in CArtAgO

CArtAgO is a platform and infrastructure providing ageneral-purpose programming model for building shared computational worlds – referred here as work environments – that agents, possibly belonging to heterogeneous agent platforms, can exploit to work together inside a Multi-Agent System. Being based on the A&A (Agents and Artifacts) conceptual model, CArtAgO work environments are modelled and engineered interms of set of artifacts programmed by MAS designers, collected in workspaces. From the agent view point, artifacts are first-class entities representing resources and tools that agents can dynamically instantiate, share and use to support their individual and collective activities. After describing the basic motivations behind the approach, the chapter provides an overview of the programming model promoted by CArtAgO for the definition of artifacts (MAS designer’s viewpoint)and for the use of artifacts(agent’s viewpoint), using Jason as reference platform for MAS programming.

The Mirror World: Preparing for Mixed-Reality Living

A new kind of smart space is emerging in which digital, physical, and social layers are strongly intertwined. These spaces extend the classic assistive functionality of ambient intelligence toward more proactive possibilities, where the smart environment not only monitors people as they perform tasks but also influences their plans and intentions. The authors explore this concept of the smart space as a mirror world, looking in particular at how it will affect our cognitive abilities and noting some of the research challenges that will need to be addressed. This department is part of a special issue on smart spaces.

Goal-Directed Interactions in Artifact-Based MAS: Jadex Agents Playing in CARTAGO Environments

In the context of cognitive agent programming frameworks, a main research effort accounts for exploiting goal-orientation for specifying and enacting agent interaction. Existing research work focuses almost totally on direct communication models, typically based on speech-acts and FIPA ACL. In this paper we focus instead on mediated interactions, and in particular on interaction taking place in artifact-based environments, where artifacts are first-class mediating tools that are used by cognitive agents in goal-directed way. The investigation is concretely supported by integrating the Jadex platform (enrolling the Belief-Desire-Intention model of agency) with the CARTAGO technology (enabling the design of artifact based environments).

Action and perception in agent programming languages: from exogenous to endogenous environments

The action and perception models adopted by state-of- the-art agent programming languages --- in the context of Multi-Agent System (MAS) programming --- have been conceived mainly to work with exogenous environments, i.e. physical or computational environments completely external to the MAS and then out of MAS design and programming. In this paper we discuss the limits of adopting such models when endogenous environments are considered, i.e. computational environments --- often referred also as application environments --- that are designed and programmed by MAS developers as a first-class abstraction to encapsulate functionalities useful for agent individual and cooperative activities. In the paper we describe an action and perception model for agent programming languages specifically conceived to be effective for endogenous environments and we discuss its evaluation using CArtAgO environment technology. On the agent side, we focus our attention on programming languages based on the BDI (Belief-Desire-Intention) model, taking Jason, 2APL and GOAL as reference case studies.

A platform for developing SOA/WS applications as open and heterogeneous multi-agent systems

In this paper we consider the use of agent-oriented models and technologies - in particular intelligent agent technologies - for the design and implementation of distributed interoperable software systems based on Service-Oriented Architecture (SOA) and Web Services (WS) standards (SOA/WS in brief). To this end, we introduce a platform called CArtAgO-WS which promotes the development of SOA/WS applications as open workspaces populated of possibly heterogeneous agents, including BDI agent platforms such as Jason and Jadex, and suitably designed artifacts as defined by the Agents and Artifacts (A & A) conceptual model. Such artifacts are used by agents as tools encapsulating basic functionalities to interact with existing Web Services, and to implement and manage Web Services. The platform is meant to be a computational environment for effectively supporting the agile experimentation of advanced agent-based SOA/WS applications, such as goal-oriented services and goal-oriented service orchestration.

Cognitive Use of Artifacts: Exploiting Relevant Information Residing in MAS Environments

Besides using language and direct communication, humans adopt various kind of artifacts as effective means to represent, store and share information, and finally support knowledge-based cooperation in complex work environments. Similarly to the human case, we argue that an analogous concept can be effective also in the context of multi-agent systems (MAS) when cognitive agents are of concern. In particular, we investigate the use of cognitive artifacts, as those computational entities designed to store, process and make available environmental resources which are relevant to achieve goals and coordinate their cooperative and distributed activities. Some of the practical benefits of the artifact-based approach are discussed through an experiment based on CArtAgO and Jason technologies. Effectiveness of different interaction strategies are investigated for teams of goal-oriented agents using different kind of comunication styles.

Facing openness with socio-cognitive trust and categories

Typical solutions for agents assessing trust relies on the circulation of information on the individual level, i.e. reputational images, subjective experiences, statistical analysis, etc. This work presents an alternative approach, inspired to the cognitive heuristics enabling humans to reason at a categorial level. The approach is envisaged as a crucial ability for agents in order to: (1) estimate trustworthiness of unknown trustees based on an ascribed membership to categories; (2) learn a series of emergent relations between trustees observable properties and their effective abilities to fulfill tasks in situated conditions. On such a basis, categorization is provided to recognize signs (Manifesta) through which hidden capabilities (Kripta) can be inferred. Learning is provided to refine reasoning attitudes needed to ascribe tasks to categories. A series of architectures combining categorization abilities, individual experiences and context awareness are evaluated and compared in simulated experiments.

Mirror Worlds as Agent Societies Situated in Mixed Reality Environments

Last years have seen the raise of several contexts such as Ambient Intelligence, Augmented Reality where Artificial Intelligence is combined with other domains such as Ubiquitous Computing, Sensor Network Technologies in order to provide proactive and responsive services to users. However, these systems are most of the times ad hoc, lacking a conceptual foundation. In this paper we provide a broad overview of mirror worlds, as physically situated agent societies, useful in particular as a framework for investigating inter-disciplinary aspects --- from cognition to interaction, cooperation, governance --- concerning future smart environments and cities shaped as large-scale mixed-reality systems.

Externalisation and internalization: a new perspective on agent modularisation in multi-agent system programming

Agent modularisation is a main issue in agent and multi-agent system programming. Existing solutions typically propose constructs such as capabilities to group and encapsulate in well-defined modules inside the agent different kinds of agent features, that depend on the architecture or model adopted—examples are goals, beliefs, intentions, skills. In this paper we introduce a further perspective, which can be considered complimentary to existing approaches, which accounts for externalizing some of such functionalities into the computational environment where agents are (logically) situated. This leads to some benefits in terms of reusability, dynamic extensibility and openness. To this end, we exploit artifact-based computational environments as introduced by the A&A meta-model and implemented in CArtAgO technology: agent modules are realised as suitably designed artifacts that agents can dynamically exploit as external tools to enhance their action repertoire and – more generally – their capability to execute tasks. Then, to let agent (and agent programmers) exploit such capabilities abstracting from the low-level mechanics of artifact management and use, we exploit the dual notion of internalization, which consists in dynamically consulting and automatically embedding high-level usage protocols described in artifact manuals as agent plans. The idea is discussed providing some practical examples of use, based on CArtAgO as technology for programming artifacts and Jason agent platform to program the agents.