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

Sull'antagonismo in vivo ed in vitro di Acremonium byssoides, endofita in Vitis vinifera, nei confronti di Plasmopara viticola

Lo studio dell\u2019interazione fra Acremonium byssoides, Vitis vinifera e Plasmopara viticola, condotto nell\u2019ultimo decennio, ha evidenziato in vitro e in vivo l\u2019attivit\ue0 antagonistica dell\u2019ifomicete, endofita negli organi verdi di alcune cultivars di vite, nei confronti del patogeno. In particolare, \ue8 stato accertato che sospensioni conidiche, filtrati colturali, estratti grezzi e metaboliti di A. byssoides riducono sensibilmente la germinazione delle spore agamiche e gamiche di P. viticola, limitando la produzione di propaguli. Inoltre, l\u2019uso di un microscopio laser confocale e l\u2019impiego di un\u2019opportuna tecnica di decolorazione dei tessuti fogliari, seguita da colorazione di contrasto, ha consentito di visualizzare l\u2019ifomicete, latente nelle nervature di foglie sane e iperparassita dell\u2019oomicete in foglie infette. In queste ultime, infatti, A. byssoides, dopo aver prodotto metaboliti secondari tossici per P. viticola, ne invade e degrada micelio, rami sporangiofori e spore gamiche. Tale attivit\ue0 antagonistica, determinando il contenimento sia della diffusione che della sopravvivenza del patogeno, pu\uf2 assumere, quindi, un ruolo rilevante nella definizione di strategie di difesa biologica contro la peronospora della vite

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

Automatic Configuration of Multi-Agent Model Predictive Controllers based on Semantic Graph World Models

We propose a shared semantic map architecture to construct and configure Model Predictive Controllers (MPC) dynamically, that solve navigation problems for multiple robotic agents sharing parts of the same environment. The navigation task is represented as a sequence of semantically labeled areas in the map, that must be traversed sequentially, i.e. a route. Each semantic label represents one or more constraints on the robots' motion behaviour in that area. The advantages of this approach are: (i) an MPC-based motion controller in each individual robot can be (re-)configured, at runtime, with the locally and temporally relevant parameters; (ii) the application can influence, also at runtime, the navigation behaviour of the robots, just by adapting the semantic labels; and (iii) the robots can reason about their need for coordination, through analyzing over which horizon in time and space their routes overlap. The paper provides simulations of various representative situations, showing that the approach of runtime configuration of the MPC drastically decreases computation time, while retaining task execution performance similar to an approach in which each robot always includes all other robots in its MPC computations

Insect oviposition in herbaceous plants attracts egg parasitoids despite fungal phytopathogen infection

Egg parasitoids are important natural enemies of several insect pests. The ability to kill the pest before it can inflict damage to the plant makes egg parasitoids ideal candidates for biological control. Several studies have shown that egg parasitoids exploit oviposition-induced plant volatiles (OIPVs) to locate host eggs laid on plant organs. Yet such studies have often overlooked that, in nature, plants frequently suffer concurrent attack by insect herbivores and phytopathogens. These dual attacks can modify the emission of induced plant volatiles, which may potentially interfere with the host location abilities of egg parasitoids. We investigated this research question using the following study organisms: the broad bean Vicia faba, the plant pathogen Stemphylium sp., the southern green stink bug Nezara viridula and its associated egg parasitoid Trissolcus basalis. We showed that T. basalis is able to exploit OPIVs in order to locate N. viridula egg masses even when V. faba plants were previously infected by Stemphylium sp. Chemical analyses indicate that the egg parasitoid ability to exploit OIPVs persists despite significant alterations of the volatile blends emitted by plants suffering multiple biotic stresses. This study highlights the importance of incorporating the complexity of multiple biotic stresses when studying parasitoid foraging behavior, in order to comprehend how to enhance the effectiveness of natural enemies in crop protection

ITalian Geomagnetic Reference Field (ITGRF): update for 2000 and secular variation model up to 2005 by autoregressive forecasting

The updated version of the ITalian Geomagnetic Reference Field (ITGRF) for 2000.0 and its secular variation model up to 2005.0 are presented in this paper. The main field model is based on a simple polynomial approximation in latitude and longitude of the geomagnetic field elements computed from IGRF on a 12° ¥ 11° grid centred over Italy. The annual means from L'Aquila observatory were used to determine the baseline level, imposing a constant observatory anomaly bias. This procedure gives a set of 6 coefficients every 5 years from 1960 to 2005 for the horizontal H, total field F, vertical Z and declination D elements of the geomagnetic field. The extrapolation of ITGRF to 2005 is based on an autoregressive forecasting of the L'Aquila observatory annual means. Comparison of the field values computed from the model with those recorded at the other Italian observatory (Castello Tesino) shows that the ITGRF improves the fit of the secular variation pattern with respect to the global IGRF model by a factor of 3. The ITGRF represents a reliable alternative to global models when reducing magnetic surveys to a common reference epoch over the Italian region