Fostering resilient execution of multi-agent plans through self-organisation

Traditional multi-agent planning addresses the coordination of multiple agents towards common goals, by producing an integrated plan of actions for each of those agents. For systems made of large numbers of cooperating agents, however, the execution and monitoring of a plan should enhance its high-level steps, possibly involving entire sub-teams, with a flexible and adaptable lower-level behaviour of the individual agents. In order to achieve such a goal, we need to integrate the behaviour dictated by a multi-agent plan with self-organizing, swarm-based approaches, capable of automatically adapting their behaviour based on the contingent situation, departing from the predetermined plan whenever needed. Moreover, in order to deal with multiple domains and unpredictable situations, the system should, as far as possible, exhibit such capabilities without hard-coding the agents behaviour and interactions. In this paper, we investigate the relationship between multi-agent planning and self-organisation through the combination of two representative approaches both enjoying declarativity. We consider a functional approach to self-organising systems development, called Aggregate Programming (AP), and propose to exploit collective adaptive behaviour to carry out plan revisions. We describe preliminary results in this direction on a case study of execution monitoring and repair of a Multi-Agent PDDL plan

A field-based computing approach to sensing-driven clustering in robot swarms

Swarm intelligence leverages collective behaviours emerging from interaction and activity of several “simple” agents to solve problems in various environments. One problem of interest in large swarms featuring a variety of sub-goals is swarm clustering, where the individuals of a swarm are assigned or choose to belong to zero or more groups, also called clusters. In this work, we address the sensing-based swarm clustering problem, where clusters are defined based on both the values sensed from the environment and the spatial distribution of the values and the agents. Moreover, we address it in a setting characterised by decentralisation of computation and interaction, and dynamicity of values and mobility of agents. For the solution, we propose to use the field-based computing paradigm, where computation and interaction are expressed in terms of a functional manipulation of fields, distributed and evolving data structures mapping each individual of the system to values over time. We devise a solution to sensing-based swarm clustering leveraging multiple concurrent field computations with limited domain and evaluate the approach experimentally by means of simulations, showing that the programmed swarms form clusters that well reflect the underlying environmental phenomena dynamics

Meaningful cut-off pain intensity for breakthrough pain changes in advanced cancer patients

Abstract OBJECTIVES: To assess the level of pain intensity at which patients feel the impetus to ask for a breakthrough cancer pain (BTcP) medication, and level of pain intensity at which patients consider they have achieved acceptable pain control after receiving a BTcP medication. METHODS: A consecutive sample of patients who were receiving oral morphine equivalents equal to or more than 60\u2009mg daily, and were prescribed rapid onset opioids for the management of episodes of BTcP, were included in the study. Focused educational activities regarding BTcP and numerical scales were established during hospital admission. At discharge patients were interviewed to find out what was the pain intensity level which gave the impetus to take the BTcP medication, what was the pain intensity for acceptable pain control after a BTcP medication had been given, and which factors prevented the patient calling for BTcP medication. A brief COPE (coping orientation to problems experienced) questionnaire was also administered. RESULTS: Fifty-two patients were recruited for this study. The meaningful pain intensity for asking for a BTcP medication was 7.1; 77% of patients had a pain intensity of 7-8 on a numerical scale of 0-10. The meaningful pain intensity for adequate analgesia after a BTcP medication was 3.5. Similarly, 77% of patients had a pain intensity of 3-4. There was no relationship with the variables examined. Concerns by patients about the use of BTcP medications were minimal. CONCLUSION: The meaningful BTcP intensity and pain intensity expected after BTcP medication can be useful in selecting patients in studies of BTcP. The principal limitation of this study was the specific setting of an acute unit with specific features and the relatively low number of patients. This observation should be followed up by further surveys with a larger number of patients and different settings

Nitrogen fertilization and arbuscular mycorrhizal fungi do not mitigate the adverse effects of soil contamination with polypropylene microfibers on maize growth

Soil contamination with microplastics may adversely affect soil properties and functions and consequently crop productivity. In this study, we wanted to verify whether the adverse effects of microplastics in the soil on maize plants (Zea mays L.) are due to a reduction in nitrogen (N) availability and a reduced capacity to establish symbiotic relationships with arbuscular mycorrhizal (AM) fungi. To do this, we performed a pot experiment in which a clayey soil was exposed to two environmentally relevant concentrations of polypropylene (PP; one of the most used plastic materials) microfibers (0.4% and 0.8% w/w) with or without the addition of N fertilizer and with or without inoculation with AM fungi. The experiment began after the soil had been incubated at 23 °C for 5 months. Soil contamination with PP considerably reduced maize root and shoot biomass, leaf area, N uptake, and N content in tissue. The adverse effects increased with the concentration of PP in the soil. Adding N to the soil did not alleviate the detrimental effects of PP on plant growth, which suggests that other factors besides N availability played a major role. Similarly, although the presence of PP did not inhibit root colonization by AM fungi (no differences were observed for this trait between the uncontaminated and PP-contaminated soils), the addition of the fungal inoculum to the soil failed to mitigate the negative impact of PP on maize growth. Quite the opposite: mycorrhization further reduced maize root biomass accumulation. Undoubtedly, much research remains to be done to shed light on the mechanisms involved in determining plant behavior in microplastic-contaminated soils, which are most likely complex. This research is a priority given the magnitude of this contamination and its potential implications for human and environmental health