Emergent group level navigation: an agent-based evaluation of movement patterns in a folivorous primate.

The foraging activity of many organisms reveal strategic movement patterns, showing efficient use of spatially distributed resources. The underlying mechanisms behind these movement patterns, such as the use of spatial memory, are topics of considerable debate. To augment existing evidence of spatial memory use in primates, we generated movement patterns from simulated primate agents with simple sensory and behavioral capabilities. We developed agents representing various hypotheses of memory use, and compared the movement patterns of simulated groups to those of an observed group of red colobus monkeys (Procolobus rufomitratus), testing for: the effects of memory type (Euclidian or landmark based), amount of memory retention, and the effects of social rules in making foraging choices at the scale of the group (independent or leader led). Our results indicate that red colobus movement patterns fit best with simulated groups that have landmark based memory and a follow the leader foraging strategy. Comparisons between simulated agents revealed that social rules had the greatest impact on a group's step length, whereas the type of memory had the highest impact on a group's path tortuosity and cohesion. Using simulation studies as experimental trials to test theories of spatial memory use allows the development of insight into the behavioral mechanisms behind animal movement, developing case-specific results, as well as general results informing how changes to perception and behavior influence movement patterns.

An architecture of multiple heterogeneous case-based reasoning employing agent technologies

This paper presents an investigation into applying Case-Based Reasoning to Multiple Heterogeneous Case Bases using agents. The adaptive CBR process and the architecture of the system are presented. A case study is presented to illustrate and evaluate the approach. The process of creating and maintaining the dynamic data structures is discussed. The similarity metrics employed by the system are used to support the process of optimisation of the collaboration between the agents which is based on the use of a blackboard architecture. The blackboard architecture is shown to support the efficient collaboration between the agents to achieve an efficient overall CBR solution, while using case-based reasoning methods to allow the overall system to adapt and “learn” new collaborative strategies for achieving the aims of the overall CBR problem solving process.

'Re-using an existing wheel' developing data architecture for cooperating autonomous and semi-autonomous, agent-based web services

This short position paper considers issues in developing Data Architecture for the Internet of Things (IoT) through the medium of an exemplar project, Domain Expertise Capture in Authoring and Development ­Environments (DECADE). A brief discussion sets the background for IoT, and the development of the ­distinction between things and computers. The paper makes a strong argument to avoid reinvention of the wheel, and to reuse approaches to distributed heterogeneous data architectures and the lessons learned from that work, and apply them to this situation. DECADE requires an autonomous recording system, ­local data storage, semi-autonomous verification model, sign-off mechanism, qualitative and ­quantitative ­analysis ­carried out when and where required through web-service architecture, based on ontology and analytic agents, with a self-maintaining ontology model. To develop this, we describe a web-service ­architecture, ­combining a distributed data warehouse, web services for analysis agents, ontology agents and a ­verification engine, with a centrally verified outcome database maintained by certifying body for qualification/­professional status.

A polysaccharide extracted from sphagnum moss as antifungal agent in archaeological conservation

On the basis of the well-known preservative properties of Sphagnum moss, a potential opportunity to use moss polysaccharides (Sphagnan) in art conservation was tested. Polysaccharides were extracted from the moss (S. palustre spp.) in the amount of 4.1% of the Sphagnum plant dry weight. All lignocelluloses were removed from this extract as a result of the treatment of the moss cellulose with sodium chlorite. The extracted polysaccharide possessed a strong acidic reaction (pH 2.8) and was soluble in water and organic solvents. The extract was tested on laboratory bacterial cultures by the disk-diffusion method. The antibacterial effect was demonstrated for E. coli and P. aeruginosa (both gram-negative) while Staphylococcus aurelus (gram-positive) was shown to be insensitive to Sphagnum polysaccharides. The antifungal effect of Sphagnum extract was tested by the disk-diffusion method on the spores of seventeen fungal species. These fungi were isolated from ethnographic museum objects and from archaeological objects excavated in the Arctic. Twelve of these isolates appeared susceptible to the extract. The inhibiting effect of the extract was also tested by the modified broth-dilution method on the most typical isolate (Aspergillus spp.). In this experiment, in one ml of the nutritious broth, 40µl of 3% solution of polysaccharides in water killed 10,000 fungal spores in 6 hours. The inhibiting effect was not connected to the acidity or osmotic effect of Sphagnum polysaccharides. As an example of the application of Sphagnum polysaccharides in art conservation, they were added as preservative agents to conservation waxes. After three weeks of exposure of microcrystalline wax to test fungi (Aspergillus spp.), 44% of wax was consumed. When, however, ~ 0.1% (w/w) of Sphagnum extract was mixed with wax, the weight loss of wax was only 4% in the same time interval. On the basis of this study it was concluded that Sphagnum moss and Sphagnum products can be recommended for use in art conservation as antifungal agents.

The Agent-Rule-Class Framework for Multi-Agent Systems

Multi-agent systems have become increasingly mature, but their appearance does not make the traditional OO approach obsolete. On the contrary, OO methodologies can benefit from the principles and tools designed for agent systems. The Agent-Rule-Class (ARC) framework is proposed as an approach that builds agents upon traditional OO system components and makes use of business rules to dictate agent behaviour with the aid of OO components. By modelling agent knowledge in business rules, the proposed paradigm provides a straightforward means to develop agent-oriented systems based on the existing object-oriented systems and offers features that are otherwise difficult to achieve in the original OO systems. The main outcome of using ARC is the achievement of adaptivity. The framework is supported by a tool that ensures agents implement up-to-date requirements from business people, reflecting desired current behaviour, without the need for frequent system rebuilds. ARC is illustrated with a rail track example.