Intelligent agents for fault tolerance: from multi-agent simulation to cluster-based implementation

Recent research in multi-agent systems incorporate fault tolerance concepts, but does not explore the extension and implementation of such ideas for large scale parallel computing systems. The work reported in this paper investigates a swarm array computing approach, namely 'Intelligent Agents'. A task to be executed on a parallel computing system is decomposed to sub-tasks and mapped onto agents that traverse an abstracted hardware layer. The agents intercommunicate across processors to share information during the event of a predicted core/processor failure and for successfully completing the task. The feasibility of the approach is validated by simulations on an FPGA using a multi-agent simulator, and implementation of a parallel reduction algorithm on a computer cluster using the Message Passing Interface.

Queue-based agent architecture for multimodal interfaces

This paper presents a queue-based agent architecture for multimodal interfaces. Using a novel approach to intelligently organise both agents and input data, this system has the potential to outperform current state-of-the-art multimodal systems, while at the same time allowing greater levels of interaction and flexibility. This assertion is supported by simulation test results showing that significant improvements can be obtained over normal sequential agent scheduling architectures. For real usage, this translates into faster, more comprehensive systems, without the limited application domain that restricts current implementations.

An agent based approach to distributed task modeling for co-operative task support

This paper describes the design and implementation of an agent based network for the support of collaborative switching tasks within the control room environment of the National Grid Company plc. This work includes aspects from several research disciplines, including operational analysis, human computer interaction, finite state modelling techniques, intelligent agents and computer supported co-operative work. Aspects of these procedures have been used in the analysis of collaborative tasks to produce distributed local models for all involved users. These models have been used as the basis for the production of local finite state automata. These automata have then been embedded within an agent network together with behavioural information extracted from the task and user analysis phase. The resulting support system is capable of task and communication management within the transmission despatch environment.

Can social interaction skills be taught by a social agent? The role of a robotic mediator in autism therapy

Increasingly socially intelligent agents (software or robotic) are used in education, rehabilitation and therapy. This paper discusses the role of interactive, mobile robots as social mediators in the particular domain of autism therapy. This research is part of the project AURORA that studies how mobile robots can be used to teach children with autism basic interaction skills that are important in social interactions among humans. Results from a particular series of trials involving pairs of two children and a mobile robot are described. The results show that the scenario with pairs of children and a robot creates a very interesting social context which gives rise to a variety of different social and non-social interaction patterns, demonstrating the specific problems but also abilities of children with autism in social interactions. Future work will include a closer analysis of interactional structure in human-human and robot-human interaction. We outline a particular framework that we are investigating.

Phase separated structures in tethered dPS–PMMA copolymer films revealed using X-ray scattering with a novel contrast enhancement agent

Tethered deuterated polystyrene-block-polymethyl methacrylate films have been examined by X-ray scattering both in their native state and following treatment with ruthenium tetroxide. The use of the stain, while increasing the thickness of the films, does not significantly alter the lateral structure or periodicity of the films and provides contrast between the two blocks. Both the periodicity of the films and the structure normal to the surface have been identified following staining. Experiments were also performed on films treated by a solvent exchange process, and the effects of staining on these films are discussed.

Principal-agent issues in asset acquisition: UK institutions and their investment agents

This paper explores principal‐agent issues in the stock selection processes of institutional property investors. Drawing upon an interview survey of fund managers and acquisition professionals, it focuses on the relationships between principals and external agents as they engage in property transactions. The research investigated the extent to which the presence of outcome‐based remuneration structures could lead to biased advice, overbidding and/or poor asset selection. It is concluded that institutional property buyers are aware of incentives for opportunistic behaviour by external agents, often have sufficient expertise to robustly evaluate agents’ advice and that these incentives are counter‐balanced by a number of important controls on potential opportunistic behaviour. There are strong counter‐incentives in the need for the agents to establish personal relationships and trust between themselves and institutional buyers, to generate repeat and related business and to preserve or generate a good reputation in the market.

Pseudomonas syringae pv. coryli, the causal agent of bacterial twig dieback of Corylus avellana

Thirty-eight bacterial strains isolated from hazelnut (Corylus avellana) cv. Tonda Gentile delle Langhe showing a twig dieback in Piedmont and Sardinia, Italy, were studied by a polyphasic approach. All strains were assessed by fatty acids analysis and repetitive sequence-based polymerase chain reaction (PCR) fingerprinting using BOX and ERIC primer sets. Representative strains also were assessed by sequencing the 16S rDNA and hrpL genes, determining the presence of the syrB gene, testing their biochemical and nutritional characteristics, and determining their pathogenicity to hazelnut and other plants species or plant organs. Moreover, they were compared with reference strains of other phytopathogenic pseudomonads. The strains from hazelnut belong to Pseudomonas syringae (sensu latu), LOPAT group Ia. Both fatty acids and repetitive-sequence-based PCR clearly discriminate such strains from other Pseudomonas spp., including P. avellanae and other P. syringae pathovars as well as P. syringae pv. syringae strains from hazelnut. Also, the sequencing of 16S rDNA and hrpL genes differentiated them from P. avellanae and from P. syringae pv. syringae. They did not possess the syrB gene. Some nutritional tests also differentiated them from related P. syringae pathovars. Upon artificial inoculation, these strains incited severe twig diebacks only on hazelnut. Our results justify the creation of a new pathovar because the strains from hazelnut constitute a homogeneous group and a discrete phenon. The name of P. syringae pv. coryli is proposed and criteria for routine identification are presented.

Synthesis and biological evaluation of a polyglutamic acid-dopamine conjugate: a new antiangiogenic agent

Dopamine has previously been shown to inhibit angiogenesis in vitro and in vivo, but its clinical applications in this context are severely limited by its short half-life. Here we report the synthesis of a polyglutamic acid-dopamine conjugate and show that conjugation significantly extends (from 1 to 24 h) dopamine’s antiangiogenic activity in vitro and in vivo. These findings form the basis for the development of a new class of agents for the treatment of angiogenesis-dependent diseases.

Queue-based agent communication architecture for intelligent human-like computer interfaces

Human-like computer interaction systems requires far more than just simple speech input/output. Such a system should communicate with the user verbally, using a conversational style language. It should be aware of its surroundings and use this context for any decisions it makes. As a synthetic character, it should have a computer generated human-like appearance. This, in turn, should be used to convey emotions, expressions and gestures. Finally, and perhaps most important of all, the system should interact with the user in real time, in a fluent and believable manner.

Towards an improved understanding of farmers' behaviour: the integrative agent-centred (IAC) framework

An effective approach to research on farmers' behaviour is based on: i) an explicit and well-motivated behavioural theory; ii) an integrative approach; and iii) understanding feedback processes and dynamics. While current approaches may effectively tackle some of them, they often fail to combine them together. The paper presents the integrative agent-centred (IAC) framework, which aims at filling this gap. It functions in accordance with these three pillars and provides a conceptual structure to understand farmers' behaviour in agricultural systems. The IAC framework is agent-centred and supports the understanding of farmers' behavior consistently with the perspective of agricultural systems as complex social-ecological systems. It combines different behavioural drivers, bridges between micro and macro levels, and depicts a potentially varied model of human agency. The use of the framework in practice is illustrated through two studies on pesticide use among smallholders in Colombia. The examples show how the framework can be implemented to derive policy implications to foster a transition towards more sustainable agricultural practices. The paper finally suggests that the framework can support different research designs for the study of agents' behaviour in agricultural and social-ecological systems.