The study of autonomous agents has a long history in the Multiagent System and the Semantic Web communities, with applications ranging from automating business processes to personal assistants. More recently, the Web of Things (WoT), which is an extension of the Internet of Things (IoT) with metadata expressed in Web standards, and its community provide further motivation for pushing the autonomous agents research agenda forward. Although representing and reasoning about norms, policies, and preferences is crucial to ensuring that autonomous agents act in a manner that satisfies stakeholder requirements, normative concepts, policies, and preferences have yet to be considered as first-class abstractions in Web-based multiagent systems. Towards this end, this article motivates the need for alignment and joint research across the Multiagent Systems, Semantic Web, and WoT communities, introduces a conceptual framework for governance of autonomous agents on the Web, and identifies several research challenges and opportunities.

We introduce a new neural network architecture that we call "grid-functioned" neural networks. It utilises a grid structure of network parameterisations that can be specialised for different subdomains of the problem, while maintaining smooth, continuous behaviour. The grid gives the user flexibility to prevent gross features from overshadowing important minor ones. We present a full characterisation of its computational and spatial complexity, and demonstrate its potential, compared to a traditional architecture, over a set of synthetic regression problems. We further illustrate the benefits through a real-world 3D skeletal animation case study, where it offers the same visual quality as a state-of-the-art model, but with lower computational complexity and better control accuracy.

VR games offer new freedom for players to interact naturally using motion. This makes it harder to design games that react to player motions convincingly. We present a framework for VR sword fighting experiences against a virtual character that simplifies the necessary technical work to achieve a convincing simulation. The framework facilitates VR design by abstracting from difficult details on the lower "physical" level of interaction, using data-driven models to automate both the identification of user actions and the synthesis of character animations. Designers are able to specify the character's behaviour on a higher "semantic" level using parameterised building blocks, which allow for control over the experience while minimising manual development work. We conducted a technical evaluation, a questionnaire study and an interactive user study. Our results suggest that the framework produces more realistic and engaging interactions than simple hand-crafted interaction logic, while supporting a controllable and understandable behaviour design.

In a normative environment, an agent’s actions are directed not only by its goals but also by the norms activated by its actions and those of other actors. The potential for conflict between agent goals and norms makes decision making challenging, in that it requires looking ahead to consider the longer-term consequences of which goal to satisfy or which norm to comply with in face of conflict. We therefore seek to determine the actions an agent should select at each point in time, taking account of its temporal goals, norms, and their conflicts. We propose a solution in which a normative planning problem is the basis for practical reasoning based on argumentation. Various types of conflict within goals, within norms, and between goals and norms are identified based on temporal properties of these entities. The properties of the best plan(s) with respect to goal achievement and norm compliance are mapped to arguments, followed by mapping their conflicts to attack between arguments, all of which are used to identify why a plan is justified.

Abstract Norms are utilised in agent societies to encourage acceptable behaviour by the participating agents. They can be established or revised from the top-down (authority) or from the bottom-up (populace). The study of norm creation from the bottom-up—or norm emergence/convergence—shows evidence of increasing activity. In consequence, we seek to analyse and categorize the approaches proposed in the literature for facilitating norm emergence. This paper makes three contributions to the study of norm emergence. Firstly, we present the different perspectives of norms and their impact on the norm emergence process, with the aim of comparing their similarities and differences in implementing the norm life cycle. Secondly, we identify the characteristics that support norm emergence that are observed in the emergence literature. Finally, we identify and propose future topics for study for the community, through a discussion of the challenges and opportunities in norm emergence.

The construction of dungeons in typical action-adventure computer games entails composing a complex arrangement of structural and temporal dependencies. It is not simple to generate dungeons with correct lock-and-key structures. In this paper we sketch a controllable approach to building graph-based models of acyclic dungeon levels via declarative constraint solving, that is capable of satisfying a range of hard gameplay and design constraints. We use a quantitative expressive range analysis to characterise the initial output of the system, present an example of the degree to which the output may be altered, and show a comparison with an alternate approach.

Normative capabilities in multi-agent systems (MAS) can be represented within agents, separately as institutions, or a blend of the two. This paper addresses how to extend the principles of open MAS to the provision of normative reasoning capabilities, which are currently either embedded in existing MAS platforms - tightly coupled and inaccessible - or not present. We use a resource-oriented architecture (ROA) pattern, that we call deontic sensors, to make normative reasoning part of an open MAS architecture. The pattern specifies how to loosely couple MAS and normative frameworks, such that each is agnostic of the other, while augmenting the brute facts that an agent perceives with institutional facts, that capture each institution's interpretation of an agent's action. In consequence, a MAS without normative capabilities can acquire them, and an embedded normative framework can be de-coupled and opened to other MAS platforms. More importantly, the deontic sensor pattern allows normative reasoning to be published as services, opening routes to certification and re-use, creation of (formalized) trust and non-specialist access to "on demand'' normative reasoning.

Social norms have a potential to contribute to advances in social intelligence. One approach to take this advantage in the design of virtual agents is the use of institutional models - a social reasoning framework which brings about social norms - in conjunction with classical AI techniques, to achieve the appropriate recognition of complex situations and provide guidance on the subsequent choice of adequate action(s) with norms. In this paper, we aim to show that the combination of an institution providing social reasoning and BDI agents providing individual reasoning, establishes a framework for socially intelligent behaviour by the interplay between: (i) the institution and Intelligent Virtual Agents (IVAs), and (ii) norms maintained by the institution and the mental states of IVAs. From an engineering point of view, the framework provides a separation of concerns because the BDI agent is augmented with the capacity to process social obligations, while the specification and verification of social structure resides in the institutional models. We illustrate our approach with two scenarios: one on queuing and another on inter-personal distance theory.

We address the problem of associating access policies with datasets and how to monitor compliance via policy-carrying data. Our contributions are a formal model in first-order logic inspired by normative multi-agent systems to regulate data access, and a computational model for the validation of specific use cases and the verification of policies against criteria. Existing work on access policy identifies roles as a key enabler, with which we concur, but much of the rest focusses on authentication and authorization technology. Our proposal aims to address the normative principles put forward in Berners-Lee’s bill of rights for the internet, through human-readable but machine-processable access control policies.

The conflicting evidence in the literature on energy feedback as a driver for energy behaviour change has lead to the realization that it is a complex problem and that interventions must be proposed and evaluated in the context of a tangled web of individual and societal factors. We put forward an integrated agent-based computational model of energy consumption behaviour change interventions based on personal values and energy literacy, informed by research in persuasive technologies, environmental, educational and cognitive psychology, sociology, and energy education. Our objectives are: (i) to build a framework to accommodate a rich variety of models that might impact consumption decisions, (ii) to use the simulation as a means to evaluate persuasive technologies in-silico prior to deployment. The model novelty lies in its capacity to connect the determinants of energy related behaviour (values, energy literacy and social practices) and several generic design strategies proposed in the area of persuasive technologies within one framework. We validate the framework using survey data and personal value and energy consumption data extracted from a 2-year field study in Exeter, UK. The preliminary evaluation results demonstrate that the model can predict energy saving behaviour much better than a random model and can correctly estimate the effect of persuasive technologies. The model can be embedded into an adaptive decision-making system for energy behaviour change.

TropICAL is a Domain Specific Language (DSL) for the description of abstract legal policies. Taking inspiration from narrative tropes, our DSL enables the creation of component “policies” that may be reused between case descriptions. These components are compiled to social institutions, which are realised in Answer Set Programming (ASP) code. In this way, the actions of defendant and plaintiff take the shape of a story which must conform to the rules in the ASP description. We propose the use of our DSL in a tool designed for lawyers to generate arguments for the argumentation process.

Security policies in organisations typically take the form of obligations for the employees. However, it is often unclear what the purpose of such obligations is, and how these can be integrated in the operational processes of the organisation. This can result in policies that may be either too strong or too weak, leading to unnecessary productivity loss, or the possibility of becoming victim to attacks that exploit the weaknesses, respectively. In this paper, we propose a framework in which the security obligations of employees are linked directly to prohibitions that prevent external agents (attackers) from reaching their goals. We use logic-based and graph-based approaches to formalise and reason about such policies, and show how the framework can be used to verify correctness of the associated refinements. Finally, we extend the graph-based model with quantitative policies and associated quantitative analysis, based on the time an adversary needs for an attack. The framework can assist organisations in aligning security policies with their threat model.

Conflicts between laws can readily arise in situations governed by different laws, a case in point being when the context of an inferior law (or set of regulations) is altered through revision of a superior law. Being able to detect these conflicts automatically and resolve them, for example by proposing revisions to one of the modelled laws or policies, would be highly beneficial for legislators, legal departments of organizations or anybody having to incorporate legal requirements into their own procedures. In this paper we present a model based approach for detecting and finding legal conflicts through a combination of a formal model of legal specifications and a computational model based on answer set programming and inductive logic programming. Given specific scenarios (descriptions of courses of action), our model-based approach can automatically detect whether these scenarios could lead to contradictory outcomes in the different legal specifications. Using these conflicts as use cases, we apply inductive logic programming (ILP) to learn revisions to the legal component that is the source of the conflict. We illustrate our approach using a case-study where a university has to change its studentship programme after the government brings in new immigration regulations.

Acting under several jurisdictions at the same time is becoming the norm rather than the exception, certainly for companies but also (sometimes without knowing) for individuals. In these circumstances disparities among the different laws are inevitable. Here, we present a mathematical and a computational model of interacting legal specifications, along with a mechanism to find conflicts between them. We illustrate the approach by a case study using European Privacy law.

Security policies in organisations typically take the form of obligations for the employees. However, it is often unclear what the purpose of such obligations is, and how these can be integrated in the operational processes of the organisation. This can result in policies that may be either too strong or too weak, leading to unnecessary productivity loss, or the possibility of becoming victim to attacks that exploit the weaknesses, respectively. In this paper, we propose a framework in which the security obligations of employees are linked directly to prohibitions that prevent external agents (attackers) from reaching their goals. We use graph-based and logic-based approaches to formalise and reason about such policies, and show how the framework can be used to verify correctness of the associated refinements. The framework can assist organisations in aligning security policies with their threat model.

ABSTRACT The use of polite agents is a new approach in order to improve efficiency and naturalism in navigation for player characters in crowded virtual worlds. This paper aims to model the politeness of virtual humans using logic‐based approaches, subject to theory of politeness decomposed of conventional and interpersonal politeness. To do so, we propose a high‐level agent architecture combined with normative framework to model and reason about ‘polite’ behaviours in social situations. With this architecture, we demonstrate (i) specifying polite behaviours as a form of social norms; (ii) generating polite behaviours using social reasoning technique; (iii) deliberation with such norms in belief–desire–intention agents; and (iv) realising physical actions based on the decision. Implementation for social reasoning is achieved by InstAL, based on the semantics of answer set programming. Using experiments with simple collision avoidance model, we show the effectiveness of polite behaviour in navigation designed by such architecture, as well as the adequacy of this architecture for modelling theory of politeness in all circumstances. Copyright © 2013 John Wiley & Sons, Ltd.

In the context of e-commerce, it is critical for a retailing company to be able to assess the market and respond quickly to changes in competition and/or service levels and availability of its products. If the company operates globally, and the geographical constraints on the supplier are different from those on the consumer, it is even more crucial to assess each market with respect to its characteristics and dynamically price every individual product accordingly. In this paper we report on an agent-based distributed system that was developed to support the retailing operations of one of the largest online book sellers in the UK, which has millions of books on offer and operates internationally in a number of market places. The system supports the collection of market data, processing of this data, and applying dynamically one of set of predefined pricing patterns. We describe the principles on which the price adaptation is based, the (long-running and proven successful) distributed scalable software architecture that supports it, illustrate how the mechanism copes with some typical situations system that arise and highlight some of the lessons learned from the development experience.

In wireless mesh networks (WMN), most routing algorithms apply broadcasting at some stage of the path discovery process. They thereby consume large chunks of the network throughput. Intelligent rebroadcast algorithms aim to reduce this overhead by calculating the usefulness of a rebroadcast and the likelihood of collisions. Unfortunately, this introduces latency and breaks the rebroadcast chain, resulting in reduced reachability. In this paper we present our Social-aware Routing Protocol with Parallel Collision Guidance Broadcasting for WMN (SCG). It reduces rebroadcasting without a loss in reachability and without a significant increase in latency. Our claims are validated through simulations comparing our algorithm with existing protocols.

We demonstrate how a subset of UML statechart diagrams (SCDs) as distinct from statecharts is encoded in the π-calculus as a number of processes which communicate via a channel-passing interaction paradigm. An extension to the original UML semantics for communicating statechart diagrams is presented. Different sorts of equivalences of UML SCDs encompassing isomorphism, strong behavioural equivalence and weak behavioural equivalence are defined. Determining equivalence of any two UML SCDs is transformed to a problem of checking whether their respective π-calculus process expressions are equivalent. The practicality of the approach is exemplified using an industry level case study.

Abstract In this paper we propose a use-case-driven iterative design methodology for normative frameworks, also called virtual institutions, which are used to govern open systems. Our computational model represents the normative framework as a logic program under answer set semantics (ASP). By means of an inductive logic programming approach, implemented using ASP, it is possible to synthesise new rules and revise the existing ones. The learning mechanism is guided by the designer who describes the desired properties of the framework through use cases, comprising (i) event traces that capture possible scenarios, and (ii) a state that describes the desired outcome. The learning process then proposes additional rules, or changes to current rules, to satisfy the constraints expressed in the use cases. Thus, the contribution of this paper is a process for the elaboration and revision of a normative framework by means of a semi-automatic and iterative process driven from specifications of (un)desirable behaviour. The process integrates a novel and general methodology for theory revision based on ASP.

Service-oriented computing is the "new wave" emerging from the growing up of web services and its adoption of elements of semantic web technology. More sophistication, in response to business requirements, does of course not make it easier to use or to control. In particular business processes demand resilience and (real-time) adaptation in the face of changing business requirements, incorporation of alternative services and finding suitable substitutes when those needed are not available. The EU-funded ALIVE project is prototyping ideas, driven by commercial and industrial uses cases, that utilize research in organizational modelling, software agents, model-driven engineering, artificial intelligence, semantic web and web services to construct tools and demonstrators to address these needs. This tutorial will focus on a use case from the ALIVE project (in one of the domains of crisis management, communications, or information services), discuss the requirements that arise from it and then explore it from the three perspectives that characterize the ALIVE approach: organizations, coordination and services, all illustrated by the innovative tools that have been developed during the project.

Service-oriented enterprise systems, which tend to be heterogeneous, loosely coupled, long-lived, and continuously running, have to cope with frequent changes to their requirements and the environment. In order to address such changes, applications need to be inherently flexible and adaptive, supported by appropriate infrastructures. In this paper, we propose a model-driven approach for the dynamic adaptation of Web services based on ontology-aware service templates. Model-driven engineering raises the level of abstraction from concrete Web service implementations to high-level service models, which leads to more flexible and automated adaptations through template designs and transformations. The ontological semantics enhances the service matching capabilities required by the dynamic adaptation process. Service templates are based on OWL-S descriptions and provide the necessary means to capture and parameterize specific behavior patterns of service models. In this paper, we apply our approach in the context of the EU-funded ALIVE project and illustrate, as an example, how the proposed framework supports the adaptation of the authentication mechanism used by an interactive tourist recommendation system.

The use of trading agents to manage the allocation and bundling of resources across computer networks is well established and literature to date has focused on a variety of auction and distributed market type mechanisms that use economic principles to determine the "best" allocation.

Service description and discovery offer complementary challenges, but in both cases, the problem is finding the right trade-off between accuracy and generality that will result in a positive service identification. Discovery systems have historically tended to focus on domain-specific techniques using single sources of knowledge to help classify queries against services, making both maintenance and extension difficult. The primary contribution of this paper is the presentation of a generic brokerage framework based on the use of plug-in components, that are themselves Web services. The framework has been developed in the context of the KNOOGLE project, where the focus has been on demonstrating support for (i) the discovery of grid services for the GridSAM job submission system and (ii) integration with the Taverna workflow enactment system. However, the broker itself is domain independent and it is the multiple user-specified matchmaker plug-ins that act as sources of domain-specific knowledge. The broker collects the results of the matchmakers' comparison of the query and service and then applies a user-specified selection policy to determine the final choice of service. Thus a range of comprehensive packaging of brokerage functionality becomes possible through the use of supplied and user-defined matchers and supplied or user-defined selection policies.

Confidentiality constraints often preclude the release of disaggregate data about individuals, which limits the types and accuracy of the results of geographical health analyses that could be done. Access to individually geocoded (disaggregate) data often involves lengthy and cumbersome procedures through review boards and committees for approval (and sometimes is not possible). Moreover, current data confidentiality-preserving solutions compatible with fine-level spatial analyses either lack flexibility or yield less than optimal results (because of confidentiality-preserving changes they introduce to disaggregate data), or both. In this paper, we present a simulation case study to illustrate how some analyses cannot be (or will suffer if) done on aggregate data. We then quickly review some existing data confidentiality-preserving techniques, and move on to explore a solution based on software agents with the potential of providing flexible, controlled (software-only) access to unmodified confidential disaggregate data and returning only results that do not expose any person-identifiable details. The solution is thus appropriate for micro-scale geographical analyses where no person-identifiable details are required in the final results (i.e., only aggregate results are needed). Our proposed software agent technique also enables post-coordinated analyses to be designed and carried out on the confidential database(s), as needed, compared to a more conventional solution based on the Web Services model that would only support a rigid, pre-coordinated (pre-determined) and rather limited set of analyses. The paper also provides an exploratory discussion of mobility, security, and trust issues associated with software agents, as well as possible directions/solutions to address these issues, including the use of virtual organizations. Successful partnerships between stakeholder organizations, proper collaboration agreements, clear policies, and unambiguous interpretations of laws and regulations are also much needed to support and ensure the success of any technological solution.

Summary form only given. Existing UML modelling tools provide only a limited support for the analysis of UML statechart diagrams. This paper describes the implementation and integration of an environment for analyzing UML statechart diagrams in two different ways. These include equivalence checking and model checking. To prove the equivalence of two statechart diagrams, we draw the two diagrams using Poseidon for UML, translate them into the pi-calculus using the SC2PiCal and check whether they are equivalent or not using the MWB. To verify the correctness of a system represented as multiple communicating statechart diagrams, we draw the diagrams using Poseidon for UML, translate them into the pi-calculus using the SC2PiCal, transform the pi-calculus expressions into equivalent NuSMV code using the PiCal2NuSMV and check the validity of the system using the NuSMV model checker.

The MONET project is a two-year investigation into mathematical web services funded by the European Commission, as part of the Information Society Technologies (IST) Programme of the Fifth Framework. The project started on 1st April 2002. The long-term aim (beyond this project) is to weave together the emerging world of web services-the semantic web-and grid computing, in that we aim to deliver sophisticated mathematical problem analysis and the code to compute the answers, for which grid services will be required, in a common open agent-based framework for the description and provision of web-based mathematical services. The short-term aim of this project is proof of concept. That is to demonstrate a framework consisting of a set of example mathematical web services together with a brokering platform used to discover and invoke these services given a query by a user to solve a particular problem.

article Object-oriented execution of OPS5 production systems Share on Authors: Mohammed H. Odeh View Profile , Julian A. Padget View Profile Authors Info & Claims ACM SIGPLAN NoticesVolume 28Issue 10Oct. 1, 1993 pp 178–190https://doi.org/10.1145/167962.165886Online:01 October 1993Publication History 3citation301DownloadsMetricsTotal Citations3Total Downloads301Last 12 Months4Last 6 weeks0 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access

Many descriptions have been published of lightweight process models for specific physical and virtual machines. On the other hand, relatively little attention has been paid to the problem of defining a model which is adequate for serious programming yet can be realized on a wide variety of architectures and maintain the semantic model across those architectures. Programming language support for concurrency models does not always address the handling or propagation of errors, nor provision for event-based programming. In this paper, we describe a model which does deal with these issues, and we present the realisation of this model in a modern object-oriented language (EuLisp). Particular attention is drawn to the contract with the programmer is architecture independence is to be assured. Hence the sentiment expressed in the title: we provide a programming model which both accommodates and delivers non-determinism on diverse platforms, and which enables the programmer to work effectively in the presence of that non-determinism.

We describe the approach to the concurrent execution of object-oriented programs that is being research at the University of Bath. The aim of this project is the concurrent execution of both new Lisp programs and existing Lisp applications. We are pursuing this goal by addressing the problems of concurrent execution at several levels: static analysis of Lisp programs as a basis for semi-automatic transformation, modification of medium-sized Lisp programs to use concurrent primitives to gain experience in their use and behaviour and the implementation of various concurrency primitives in a compiled distributed heterogeneous Lisp environment. Each of these topics is described in turn and its relationship to the long term aim defined above is examined.

We describe the development of a formal power series expansion package for Reduce which takes advantage of Reduce's domain mechanism to make for a seamless integration of series values with the rest of the Reduce system. Consequently, series values may be manipulated with the same algebraic operators as other algebraic objects. To create the illusion of infinite power series a simulated lazy-evaluation mechanism has been used. This paper reports our experience of using the Reduce domain mechanism and documents the algorithms and data structures that can be used to implement and to represent power series.

This paper considers current solutions to the problem of representing multiple environments, and uses the results to develop a new model. The motivation is partly a consequence of the renewed interest in the more sophisticated forms of access and control [Sussman & Steele 1978], [Smith 1983]. [Friedman et al. 1984], and partly because the problem identified by Moses [1970] has not, as yet, been satisfactorily resolved. The new model is derived from a consideration of the semantics of identifier binding interrogation. The implementation itself rests on the existence of an environment labeling function which solves a variant of a well known graph theory problem called nearest common ancestor. We describe a suitable implementation of such a function. The new scheme has been implemented in two different LISP systems (Cambridge LISP and Portable Standard LISP), and a third (LISP/VM) is under consideration. In addition, pure deep binding and full shallow binding have both been implemented on top the same base system (Cambridge LISP). Thus it is possible to collect comparisons of the relative efficiencies running simple (stack behavior) programs and complex (multiple context) programs. Some timing results for various tests are given in the final section.