Autonomous multiagent systems can be used in different domains such as agriculture, search and rescue, and fire protection because they can accomplish large missions more quickly and robustly by dividing them into separate tasks. Using multiple agents introduces additional complexity, which makes autonomous reasoning and decision making more challenging, however. Because agents such as ground robots, unmanned air vehicles, and autonomous underwater vehicles may have limited computational resources, they may need computationally efficient yet powerful reasoning algorithms (decision-making processes that perform deliberation and means-end reasoning). Metareasoning, which is reasoning about these reasoning algorithms, offers a way to tackle these challenges by monitoring and controlling reasoning algorithms to improve agent and system performance. Although metareasoning approaches for individual computational agents have been studied, no survey of metareasoning in multiagent systems (MAS) has yet appeared. This survey fills the existing gap by discussing the multiagent metareasoning approaches that have been studied in the literature. It identifies metareasoning structures, applications of metareasoning to reasoning problems, and the modes (techniques) used to control reasoning processes. This survey contributes to the study of MAS by providing a framework for discussing multiagent metareasoning, highlighting successful approaches, and indicating areas where future work may be fruitful.
Tidal stream environments exhibit fast current flows and unique turbulent features occurring at fine spatio-temporal scales (metres and seconds). There is now global recognition of the importance of tidal stream environments for marine megafauna. Such areas are also key to the development of marine renewable energy due to the reliable and predictable nature of tidally driven flows. Bed-derived turbulent features, such as kolk-boils, transport organic material to the surface and may increase the availability of prey species (fish) for foraging marine megafauna (seabirds and marine mammals). Quantification of animal association and interactions with turbulent features is required to understand potential environmental impacts of tidal energy developments in these sites. Downward-facing unmanned aerial vehicle (UAV) imagery was collected within the Pentland Firth, UK. Resulting imagery was used to quantify the density distribution of pursuit-diving seabirds, called auks (of the family Alcidae), distribution in comparison relation to concurrent surface imagery of kolk-boils and, analyse evaluate spatial relationships with individual kolk-boil features, and quantify body orientation relative to the water flow. Although variability was present, auk density distribution was generally correlated with that of kolk-boils throughout the study area; however, spatial analysis highlighted an overall trend of finer-scale dispersion between individual auks and kolk-boils. Auk orientation on the surface was primarily observed across the flow throughout ebb and flood tidal phases. These results suggest that auks may be associating with kolk-boil peripheries. Similarly, it may be energetically beneficial to orientate across the flow while maintaining observation of current flow or searching for shallow prey species and potential threats in the environment. This work demonstrates that UAV imagery was appropriate for quantification of fine-scale biophysical interactions. It allowed for concurrent measurement of hydrodynamic and predator metrics in a challenging environment and provided novel insights not possible to collect by conventional survey methodology. This technique can increase the evidence base for assessment of potential impacts of marine renewable energy extraction on key marine species.
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