394 research outputs found

    Explaining Failures Propagations in the Execution of Multi-Agent Temporal Plans

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

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    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

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    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

    Posttraumatic Growth in Breast Cancer Survivors: Are Depressive Symptoms Really Negative Predictors?

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    Objective: Breast cancer (BC) diagnosis is a potentially traumatic event, the related challenges of which can trigger positive or negative reactions. Posttraumatic growth (PTG) is defined as a positive psychological change experienced as a result of the struggle. The present study aimed to shed light on the relationship between the evolution of depressive symptoms over time and PTG in a group of BC survivors. Method: Depressive symptoms at the time of diagnosis (T0) and 2 years later (T1) were evaluated to investigate their potential impact on the level of PTG at T1. A total of 147 BC patients were recruited and divided into 4 groups according to the changes in depressive symptoms they experienced over time (patients who were never depressed, no longer depressed, still depressed, and depressed now). A One-way analysis of variance was run to compare the levels of PTG for the four groups. Results: The One-way analysis of variance showed that PTG score was significantly different among groups with different levels of depressive symptoms (p .008). Post hoc comparisons indicated that the PTG score was statistically significantly higher in the no longer depressed group compared with the still depressed and depressed now groups. Conclusions: The current results suggest that high levels of depressive symptoms, displayed at the time of cancer diagnosis, can be considered catalysts for PTG at follow-up, on condition that women experience elevated depressive symptoms only in the first period of the disease

    Anxiety and depression in rheumatologic diseases: the relevance of diagnosis and management

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    The high prevalence of emotional disorders (anxiety, chronic stress, mood depression) in patients with pain during rheumatologic diseases (particularly fibromyalgia) is closely related to the common pathogenic mechanisms concerning emotions and pain. Therefore a prompt identification of any psychic component of pain, also by means of specific tools, is a must, because it can require an adjustment of the therapeutic approach by combining both an analgesic treatment and antidepressants and/or psychotherapeutic strategies

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

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    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
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