259 research outputs found

    Towards a Reformulation Based Approach for Efficient Numeric Planning: Numeric Outer Entanglements

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    Restricting the search space has shown to be an effective approach for improving the performance of automated planning systems. A planner-independent technique for pruning the search space is domain and problem reformulation. Recently, Outer Entanglements, which are relations between planning operators and initial or goal predicates, have been introduced as a reformulation technique for eliminating potential undesirable instances of planning operators, and thus restricting the search space. Reformulation techniques, however, have been mainly applied in classical planning, although many real-world planning applications require to deal with numerical information. In this paper, we investigate the usefulness of reformulation approaches in planning with numerical fluents. In particular, we propose and extension of the notion of outer entanglements for handling numeric fluents. An empirical evaluation, which involves 150 instances from 5 domains, shows promising results

    Numerical Integration and Dynamic Discretization in Heuristic Search Planning over Hybrid Domains

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    In this paper we look into the problem of planning over hybrid domains, where change can be both discrete and instantaneous, or continuous over time. In addition, it is required that each state on the trajectory induced by the execution of plans complies with a given set of global constraints. We approach the computation of plans for such domains as the problem of searching over a deterministic state model. In this model, some of the successor states are obtained by solving numerically the so-called initial value problem over a set of ordinary differential equations (ODE) given by the current plan prefix. These equations hold over time intervals whose duration is determined dynamically, according to whether zero crossing events take place for a set of invariant conditions. The resulting planner, FS+, incorporates these features together with effective heuristic guidance. FS+ does not impose any of the syntactic restrictions on process effects often found on the existing literature on Hybrid Planning. A key concept of our approach is that a clear separation is struck between planning and simulation time steps. The former is the time allowed to observe the evolution of a given dynamical system before committing to a future course of action, whilst the later is part of the model of the environment. FS+ is shown to be a robust planner over a diverse set of hybrid domains, taken from the existing literature on hybrid planning and systems.Comment: 17 page

    Proactive and Reactive Reconfiguration for the Robust Execution of Multi Modality Plans

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    The paper addresses the problem of executing a plan in a dynamic environment for tasks involving constraints on consumable resources modeled as numeric fluents. In particular, the paper proposes a novel monitoring and adaptation strategy joining reactivity and proactivity in a unified framework. By exploiting the flexibility of a multi modality plan (where each action can be executed in different modalities), reactivity and proactivity are guaranteed by means of a reconfiguration step. The reconfiguration is performed (i) when the plan is no more valid to recovery from the impasse (reactively), or (ii) under the lead of a kernel based strategy to enforce the tolerance to unexpected situations (proactivity). Both mechanisms have been integrated into a continual planning system and experimentally evaluated over three numeric domains, extensions of planning competition domains. Results show that the approach is able to increase the percentage of cases successfully solved while preserving efficiency in most situations

    Interval-Based Relaxation for General Numeric Planning

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    We generalise the interval-based relaxation to sequential numeric planning problems with non-linear conditions and effects, and cyclic dependencies. This effectively removes all the limitations on the problem placed in previous work on numeric planning heuristics, and even allows us to extend the planning language with a wider set of mathematical functions. Heuristics obtained from the generalised relaxation are pruning-safe. We derive one such heuristic and use it to solve discrete-time control-like planning problems with autonomous processes. Few planners can solve such problems, and search with our new heuristic compares favourably with the

    The aftermath of the Merck's HIV vaccine trial

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    The recently released results of the Merck's Phase IIb "test-of concept" vaccine trials have shown no protection from HIV-1 infection in the vaccinated group compared with a control group vaccinated with placebo. The study was designed to test the Merck's MRKAd5 trivalent candidate vaccine. The vaccine formulation was expected to stimulate a HIV-specific T cell immune response and to either prevent infection, or to reduce the levels of the viral load in vaccinated subjects. Upon the first evaluation of the interim data, the independent Data and Safety Monitoring Board (DSMB) underscored no protection from HIV-1 infection in the vaccine-inoculated volunteers compared with the control group; accordingly, the vaccine trial was stopped. This disappointing outcome warrants a critical analysis of the current vaccine studies and calls for a renewed effort toward a rational design of novel immunogens to be tested in large primate trials

    Loss of the candidate tumor suppressor ZEB1 (TCF8, ZFHX1A) in SĂ©zary syndrome

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    Cutaneous T-cell lymphoma is a group of incurable extranodal non-Hodgkin lymphomas that develop from the skin-homing CD4+ T cell. Mycosis fungoides and SĂ©zary syndrome are the most common histological subtypes. Although next-generation sequencing data provided significant advances in the comprehension of the genetic basis of this lymphoma, there is not uniform consensus on the identity and prevalence of putative driver genes for this heterogeneous group of tumors. Additional studies may increase the knowledge about the complex genetic etiology characterizing this lymphoma. We used SNP6 arrays and GISTIC algorithm to prioritize a list of focal somatic copy-number alterations in a dataset of multiple sequential samples from 21 SĂ©zary syndrome patients. Our results confirmed a prevalence of significant focal deletions over amplifications: single well-known tumor suppressors, such as TP53, PTEN, and RB1, are targeted by these aberrations. In our cohort, ZEB1 (TCF8, ZFHX1A) spans a deletion having the highest level of significance. In a larger group of 43 patients, we found that ZEB1 is affected by deletions and somatic inactivating mutations in 46.5% of cases; also, we found potentially relevant ZEB1 germline variants. The survival analysis shows a worse clinical course for patients with ZEB1 biallelic inactivation. Multiple abnormal expression signatures were found associated with ZEB1 depletion in SĂ©zary patients we verified that ZEB1 exerts a role in oxidative response of SĂ©zary cells. Our data confirm the importance of deletions in the pathogenesis of cutaneous T-cell lymphoma. The characterization of ZEB1 abnormalities in SĂ©zary syndrome fulfils the criteria of a canonical tumor suppressor gene. Although additional confirmations are needed, our findings suggest, for the first time, that ZEB1 germline variants might contribute to the risk of developing this disease. Also, we provide evidence that ZEB1 activity in SĂ©zary cells, influencing the reactive oxygen species production, affects cell viability and apoptosis

    Involving the Human User in the Control Architecture of an Autonomous Agent

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    Abstract. The paper presents an architecture for an autonomous robotic agent, which carries on a plan in a partially observable environment. A Supervisor module is in charge of assuring the correct execution of the plan, possibly by inferring alternative recovery plans when unexpected contingencies occur. In the present paper we describe a control strategy where a human user is directly involved in the control loop, and plays the role of advisor by helping the robotic agent both for reducing ambiguity in the robot's observations, and for selecting the preferred recovery plan
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