Towards Dynamic Agent Interaction Support in Open Multiagent Systems

In open multi-agent systems, linked data enables agents to communicate with each other and to gather knowledge for autonomous decision. Until now, trust is a factor for starting communications and ignores doubts about the content or context of ongoing communications. Several approaches are used to identify whom to trust and how human trust can be computationally modeled. Yet, they do not consider a change of context or of other agents’ behavior at runtime. The proposed doctoral work aims to support content- and context-related trust in open multi-agent systems using linked data. Existing trust models need to be surveyed with respect to content- and context-related trust. A framework based on a fitting trust model and working with linked data must be developed to establish and dynamically refine trust relationships on the autonomous agents’ point of view. This would enhance the applicability of decentralized systems without introducing central units as the history of the web demonstrates. Web engineers are hereby supported to work on a new level of abstraction using the decentralization, but not scrutinizing specific communication sequences.

The paper presents an abstract architecture specifically addressed for the design of open multi-agent systems (MAS) and virtual organizations. The proposal takes into account all the components to cover the characteristics and needs for systems of this kind. This architecture has been called THOMAS (MeTHods, Techniques and Tools for Open Multi-Agent Systems) and consists of a set of modular services.

Software agents’ ability to interact within different open systems, designed by different groups, presupposes an agreement on an unambiguous definition of a set of concepts, used to describe the context of the interaction and the communication language the agents can use. Agents’ interactions ought to allow for reliable expectations on the possible evolution of the system; however, in open systems interacting agents may not conform to predefined specifications. A possible solution is to define interaction environments including a normative component, with suitable rules to regulate the behaviour of agents. To tackle this problem we propose an application-independent metamodel of artificial institutions that can be used to define open multiagent systems. In our view an artificial institution is made up by an ontology that models the social context of the interaction, a set of authorizations to act on the institutional context, a set of linguistic conventions for the performance of institutional actions and a system of norms that are necessary to constrain the agents’ actions.

Agents frequently collaborate to achieve a shared goal or to accomplish a task that they cannot do alone. However, collaboration is difficult in open multi-agent systems where agents share constrained resources to achieve both individual and shared goals. In current approaches to collaboration, agents are organised into disjoint groups and social reasoning is used to capture their capabilities when selecting a qualified set of collaborators. These approaches are not useful when agents are in multiple, overlapping groups; depend on each other when using shared resources; have multiple goals to achieve simultaneously; and have to share the overall costs and benefits. In this article, agents use social reasoning to enhance their understanding of other agents’ goals and their dependencies, and self-adaptive techniques to adapt their level of self-interest in a collaborative process, with a view to contributing to lowering shared costs or increasing shared benefits. This model aims at improving the extent to which agents’ goals are met while improving shared resource usage efficiency. For example, in a public transport system where each mode of transport has limited capacity, commuters will be enabled to make choices that avoid over-capacity in different modes, or in a smart energy grid with limited capacity, users can make choices as to when they increase their demand. The model simultaneously helps avoid overloading a shared resource while allowing users to achieve their own goals. The proposed model is evaluated in an open multi-agent system with 100 agents operating in multiple overlapping groups and sharing multiple constrained resources. The impact of agents’ varying levels of social dependencies, mobility, and their groups’ density on their individual and shared goal achievement is analysed.

Resilience to fire and climate seasonality drive the temporal dynamics of ant-plant interactions in a fire-prone ecosystem

In open multi-agent systems trust is necessary to improve cooperation by enabling agents to choose good partners. Most trust models work by taking, in addition to direct experiences, other agents' communicated evaluations into account. However, in an open multi-agent system other agents may use different trust models and as such the evaluations they communicate are based on different principles. This article shows that trust alignment is a crucial tool in this communication. Furthermore we show that trust alignment improves significantly if the description of the evidence, upon which a trust evaluation is based, is taken into account.

G protein-gated inwardly rectifying potassium (GIRK) channels control neuronal excitability in the brain and are implicated in several different neurological diseases. The anionic phospholipid phosphatidylinositol 4,5 bisphosphate (PIP2) is an essential cofactor for GIRK channel gating, but the precise mechanism by which PIP2 opens GIRK channels remains poorly understood. Previous structural studies have revealed several highly conserved, positively charged residues in the "tether helix" (C-linker) that interact with the negatively charged PIP2 However, these crystal structures of neuronal GIRK channels in complex with PIP2 provide only snapshots of PIP2's interaction with the channel and thus lack details about the gating transitions triggered by PIP2 binding. Here, our functional studies reveal that one of these conserved basic residues in GIRK2, Lys200 (6'K), supports a complex and dynamic interaction with PIP2 When Lys200 is mutated to an uncharged amino acid, it activates the channel by enhancing the interaction with PIP2 Atomistic molecular dynamic simulations of neuronal GIRK2 with the same 6' substitution reveal an open GIRK2 channel with PIP2 molecules adopting novel positions. This dynamic interaction with PIP2 may explain the intrinsic low open probability of GIRK channels and the mechanism underlying activation by G protein Gβγ subunits and ethanol.

In this paper we argue that open multi-agent systems can be effectively designed and implemented as electronic institutions composed of a vast number of heterogeneous (human and software) agents playing different roles and interacting by means of speech acts. Thus taking inspiration from traditional human institutions, we offer a general agent-mediated computational model of institutions that serves to realise an actual agent-mediated electronic auction house where heterogeneous agents can trade.

Open systems are complex, heterogeneous systems whose complexity is often handled by component-based approaches. While the internal functioning of such components is invisible to the outside, a great emphasis is put on the verification of properties that ensure a safe, predictable, and understandable external behaviour. At the same time, the rules that govern and describe the system behaviour must guarantee maximum flexibility. Developing technologies that can satisfy the requirements of open multi-agent systems poses an important and difficult challenge. Here, declarative approaches have the potential of offering solutions satisfying the needs for both specifying and developing open multi-agent systems and other open systems for diverse applications such as business processes, clinical guidelines and cloud computing.KeywordsCloud ComputingBusiness ProcessMultiagent SystemInternal FunctioningBusiness Process ManagementThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

This article draws attention to language choice and language use of Austrian bi- and multilingual school children. We explore some implications of their linguistic practices with regard to social inclusion in an Austrian educational school setting. Pursuing a Dynamic Systems and Complexity Theory approach, we hypothesise that before language users actually use a language within a certain context, they have to evaluate the respective communicative situation by taking multiple contextual factors into consideration, meaning language users choose to use, or not to use, a language based on the socio-contextual information at hand. We consider these contextual factors to be most relevant as they provide the basis on which speakers can actually make use of a certain language within a given context. By drawing on examples of empirical data obtained through a language background survey, we examine some of the complex and dynamic interactions of contextual parameters influencing language choice and language use in the formal educational setting of classroom instruction. Based on the results of this study, we display a selection of the dynamic and complex interactions of pupils’ language use in one specific context as well as their language preferences and how these relate to social inclusion.

Marine algae provide a suitable habitat for a wide range of mobile and sessile macrofauna. Many of these organisms are permanent members of the epiphyton, whereas others utilize the host in a more transient fashion. Different types of algae support different suites of epiphytes according to the resources which the former provide. These include food and shelter as well as surfaces for attachment. Although some epiphytes are beneficial, others may impose a high selective cost on their host algae. Consequently the dynamic interactions between algae and their epiphytes are often extremely complex and not easy to categorize. In general, algae attempt to maximize associations with beneficial epiphytes and minimize encounters with those which impose excessive cost. Such complex interactions and the often close interdependence of epiphytes and host suggest a considerable degree of coevolution, though at present there is little conclusive evidence for this. This intriguing yet surprisingly neglected field of coastal ecology is clearly one which merits further detailed study.

Roles are an important concept used for different purposes like the modeling of organizational structure of multi-agent systems, the modeling of protocols, and as basic building blocks for defining the behavior of agents. Modeling interactions by roles gives several advantages, the most important of which is the separation of concerns by distinguishing the agent-level and system-level with regard to interaction. However, in open MASs, the composition of independently developed roles may lead to unexpected emergent behavior of the agents. This paper identifies requirements for modeling role-based interactions, and presents a formal specification model of roles for complex interactions. Our approach aims to integrate specification and verification into the Component Based Development (CBD) of roles. An application example of interactions protocols is given to illustrate our formal framework.

Coordinating Agents in Organizations Using Social Commitments

In open multi-agent systems, agents are mobile and may leave or enter the system. This dynamicity results in two closely related agent communication problems, namely, efficient message passing and service agent discovery. This paper describes how these problems are addressed in the Actor Architecture (AA). Agents in AA obey the operational semantics of actors, and the architecture is designed to support large-scale open multi-agent systems. Efficient message passing is facilitated by the use of dynamic names: a part of the mobile agent name is a function of the platform that currently hosts the agent. To facilitate service agent discovery, middle agents support application agent-oriented matchmaking and brokering services. The middle agents may accept search objects to enable customization of searches; this reduces communication overhead in discovering service agents when the matching criteria are complex. The use of mobile search objects creates a security threat, as codes developed by different groups may be moved to the same middle agent. This threat is mitigated by restricting which operations a migrated object is allowed to perform. We describes an empirical evaluation of these ideas using a large scale multi-agent UAV (Unmanned Aerial Vehicle) simulation that was developed using AA.

Norms are dynamic entities that exist in open multi-agent systems to control agents' behavior. For norms to be effective in a domain, agents must first detect the norms' existence. Recent works in this area have proposed mechanisms to endow agents with a norm detection capability. However, existing works in norms detection entail agents to consider only one norm in a particular event. In reality, one event may have more than one set of norms existing in a domain. In a more recent study, a norm detection mechanism reports that more than one norm can co-exist in a society. Thus, we argue that the existing approaches do not help agents to decide which norms to adopt in cases of multiple norms. To solve this problem, we propose the concept of norms trust to help agents to decide which detected norms are trustable from a set of norms that exist in an environment. The proposed trust-based norms evaluation consists of two-tier assessment; a credible agent evaluation that involves the task of evaluating the neighboring agents' trust and a norms trust evaluation which is the aggregation of norm adoption ratio, norm adoption risk, and norms salience. The evaluation framework is then reinforced with a working scenario to illustrate the process.