Uncertainty in Soft Temporal Constraint Problems:A General Framework and Controllability Algorithms forThe Fuzzy Case

In real-life temporal scenarios, uncertainty and preferences are often essential and coexisting aspects. We present a formalism where quantitative temporal constraints with both preferences and uncertainty can be defined. We show how three classical notions of controllability (that is, strong, weak, and dynamic), which have been developed for uncertain temporal problems, can be generalized to handle preferences as well. After defining this general framework, we focus on problems where preferences follow the fuzzy approach, and with properties that assure tractability. For such problems, we propose algorithms to check the presence of the controllability properties. In particular, we show that in such a setting dealing simultaneously with preferences and uncertainty does not increase the complexity of controllability testing. We also develop a dynamic execution algorithm, of polynomial complexity, that produces temporal plans under uncertainty that are optimal with respect to fuzzy preferences

Certainty Closure: Reliable Constraint Reasoning with Incomplete or Erroneous Data

Constraint Programming (CP) has proved an effective paradigm to model and solve difficult combinatorial satisfaction and optimisation problems from disparate domains. Many such problems arising from the commercial world are permeated by data uncertainty. Existing CP approaches that accommodate uncertainty are less suited to uncertainty arising due to incomplete and erroneous data, because they do not build reliable models and solutions guaranteed to address the user's genuine problem as she perceives it. Other fields such as reliable computation offer combinations of models and associated methods to handle these types of uncertain data, but lack an expressive framework characterising the resolution methodology independently of the model. We present a unifying framework that extends the CP formalism in both model and solutions, to tackle ill-defined combinatorial problems with incomplete or erroneous data. The certainty closure framework brings together modelling and solving methodologies from different fields into the CP paradigm to provide reliable and efficient approches for uncertain constraint problems. We demonstrate the applicability of the framework on a case study in network diagnosis. We define resolution forms that give generic templates, and their associated operational semantics, to derive practical solution methods for reliable solutions.Comment: Revised versio

Towards quantifying the completeness of BDI goals

Often, such as in the presence of con icts, an agent must choose between multiple intentions. The level of complete- ness of the intentions can be a factor in this deliberation. We sketch a pragmatic but principled mechanism for quan- tifying the level of completeness of goals in a Belief-Desire- Intention{like agent. Our approach leverages previous work on resource and e ects summarization but we go beyond by accommodating both dynamic resource summaries and goal e ects, while also allowing a non-binary quanti cation of goal completeness

Toward Understanding Massive Star Formation

Although fundamental for astrophysics, the processes that produce massive stars are not well understood. Large distances, high extinction, and short timescales of critical evolutionary phases make observations of these processes challenging. Lacking good observational guidance, theoretical models have remained controversial. This review offers a basic description of the collapse of a massive molecular core and a critical discussion of the three competing concepts of massive star formation: - monolithic collapse in isolated cores - competitive accretion in a protocluster environment - stellar collisions and mergers in very dense systems We also review the observed outflows, multiplicity, and clustering properties of massive stars, the upper initial mass function and the upper mass limit. We conclude that high-mass star formation is not merely a scaled-up version of low-mass star formation with higher accretion rates, but partly a mechanism of its own, primarily owing to the role of stellar mass and radiation pressure in controlling the dynamics.Comment: 139 pages, 18 figures, 5 tables, glossar

Towards optimal demand-side bidding in parallel auctions for time-shiftable electrical loads

Increasing electricity production from renewableenergy sources has, by its fluctuating nature, created the need for more flexible demand side management. How to integrate flexible demand in the electricity system is an open research question. We consider the case of procuring the energy needs of a time-shiftable load through a set of simultaneous second price auctions. We derive a required condition for optimal bidding strategies. We then show the following results and bidding strategies under different market assumptions. For identical uniform auctions and multiple units of demand, we show that the global optimal strategy is to bid uniformly across all auctions. For non-identical auctions and multiple units, we provide a way to find solutions through a recursive approach and a non-linear solver. We show that our approach outperforms the literature under higher uncertainty conditions

Probing the close environment of massive young stars with spectro-astrometry

Aims: We test the technique of spectro-astrometry as a potential method to investigate the close environment of massive young stars. Method: Archival VLT near infrared K band spectra (R=8900) of three massive young stellar objects and one Wolf-Rayet star are examined for spectro-astrometric signatures. The young stellar objects display emission lines such as Brackett gamma, CO 2-0 and CO 3-1 that are characteristic of ionised regions and molecular disks respectively. Two of the sample sources also display emission lines such as NIII and MgII that are characteristic of high temperatures. Results: Most of the emission lines show spectro-astrometric signal at various levels resulting in different positional displacements. The shapes and magnitudes of the positional displacements imply the presence of large disk/envelopes in emission and expanding shells of ionised gas. The results obtained for the source 18006-2422nr766 in particular provide larger estimates (> 300AU) on CO emitting regions indicating that in MYSOs CO may arise from inner regions of extended dense envelopes as well. Conclusions: The overall results from this study demonstrate the utility of spectro-astrometry as a potential method to constrain the sizes of various physical entities such as disks/envelopes, UCHII regions and/or ionised shells in the close environment of a massive young star.Comment: 4 pages, 4 figures, 1 tabl

Finding robust solutions for constraint satisfaction problems with discrete and ordered domains by coverings

Constraint programming is a paradigm wherein relations between variables are stated in the form of constraints. Many real life problems come from uncertain and dynamic environments, where the initial constraints and domains may change during its execution. Thus, the solution found for the problem may become invalid. The search forrobustsolutions for constraint satisfaction problems (CSPs) has become an important issue in the ¿eld of constraint programming. In some cases, there exists knowledge about the uncertain and dynamic environment. In other cases, this information is unknown or hard to obtain. In this paper, we consider CSPs with discrete and ordered domains where changes only involve restrictions or expansions of domains or constraints. To this end, we model CSPs as weighted CSPs (WCSPs) by assigning weights to each valid tuple of the problem constraints and domains. The weight of each valid tuple is based on its distance from the borders of the space of valid tuples in the corresponding constraint/domain. This distance is estimated by a new concept introduced in this paper: coverings. Thus, the best solution for the modeled WCSP can be considered as a most robust solution for the original CSP according to these assumptionsThis work has been partially supported by the research projects TIN2010-20976-C02-01 (Min. de Ciencia e Innovacion, Spain) and P19/08 (Min. de Fomento, Spain-FEDER), and the fellowship program FPU.Climent Aunés, LI.; Wallace, RJ.; Salido Gregorio, MA.; Barber Sanchís, F. (2013). Finding robust solutions for constraint satisfaction problems with discrete and ordered domains by coverings. Artificial Intelligence Review. 1-26. https://doi.org/10.1007/s10462-013-9420-0S126Climent L, Salido M, Barber F (2011) Reformulating dynamic linear constraint satisfaction problems as weighted csps for searching robust solutions. In: Ninth symposium of abstraction, reformulation, and approximation (SARA-11), pp 34–41Dechter R, Dechter A (1988) Belief maintenance in dynamic constraint networks. In: Proceedings of the 7th national conference on, artificial intelligence (AAAI-88), pp 37–42Dechter R, Meiri I, Pearl J (1991) Temporal constraint networks. Artif Intell 49(1):61–95Fargier H, Lang J (1993) Uncertainty in constraint satisfaction problems: a probabilistic approach. In: Proceedings of the symbolic and quantitative approaches to reasoning and uncertainty (EC-SQARU-93), pp 97–104Fargier H, Lang J, Schiex T (1996) Mixed constraint satisfaction: a framework for decision problems under incomplete knowledge. In: Proceedings of the 13th national conference on, artificial intelligence, pp 175–180Fowler D, Brown K (2000) Branching constraint satisfaction problems for solutions robust under likely changes. In: Proceedings of the international conference on principles and practice of constraint programming (CP-2000), pp 500–504Goles E, Martínez S (1990) Neural and automata networks: dynamical behavior and applications. Kluwer Academic Publishers, DordrechtHays W (1973) Statistics for the social sciences, vol 410, 2nd edn. Holt, Rinehart and Winston, New YorkHebrard E (2006) Robust solutions for constraint satisfaction and optimisation under uncertainty. PhD thesis, University of New South WalesHerrmann H, Schneider C, Moreira A, Andrade Jr J, Havlin S (2011) Onion-like network topology enhances robustness against malicious attacks. J Stat Mech Theory Exp 2011(1):P01,027Larrosa J, Schiex T (2004) Solving weighted CSP by maintaining arc consistency. Artif Intell 159:1–26Larrosa J, Meseguer P, Schiex T (1999) Maintaining reversible DAC for Max-CSP. J Artif Intell 107(1):149–163Mackworth A (1977) On reading sketch maps. In: Proceedings of IJCAI’77, pp 598–606Sam J (1995) Constraint consistency techniques for continuous domains. These de doctorat, École polytechnique fédérale de LausanneSchiex T, Fargier H, Verfaillie G (1995) Valued constraint satisfaction problems: hard and easy problems. In: Proceedings of the 14th international joint conference on, artificial intelligence (IJCAI-95), pp 631–637Taillard E (1993) Benchmarks for basic scheduling problems. Eur J Oper Res 64(2):278–285Verfaillie G, Jussien N (2005) Constraint solving in uncertain and dynamic environments: a survey. Constraints 10(3):253–281Wallace R, Freuder E (1998) Stable solutions for dynamic constraint satisfaction problems. In: Proceedings of the 4th international conference on principles and practice of constraint programming (CP-98), pp 447–461Wallace RJ, Grimes D (2010) Problem-structure versus solution-based methods for solving dynamic constraint satisfaction problems. In: Proceedings of the 22nd international conference on tools with artificial intelligence (ICTAI-10), IEEEWalsh T (2002) Stochastic constraint programming. In: Proceedings of the 15th European conference on, artificial intelligence (ECAI-02), pp 111–115William F (2006) Topology and its applications. Wiley, New YorkWiner B (1971) Statistical principles in experimental design, 2nd edn. McGraw-Hill, New YorkYorke-Smith N, Gervet C (2009) Certainty closure: reliable constraint reasoning with incomplete or erroneous data. J ACM Trans Comput Log (TOCL) 10(1):

Fragmentation and mass segregation in the massive dense cores of Cygnus X

We present Plateau de Bure interferometer observations obtained in continuum at 1.3 and 3.5 mm towards the six most massive and young (IR-quiet) dense cores in Cygnus X. Located at only 1.7 kpc, the Cygnus X region offers the opportunity of reaching small enough scales (of the order of 1700 AU at 1.3 mm) to separate individual collapsing objects. The cores are sub-fragmented with a total of 23 fragments inside 5 cores. Only the most compact core, CygX-N63, could actually be a single massive protostar with an envelope mass as large as 60 Msun. The fragments in the other cores have sizes and separations similar to low-mass pre-stellar and proto-stellar condensations in nearby protoclusters, and are probably of the same nature. A total of 9 out of these 23 protostellar objects are found to be probable precursors of OB stars with envelope masses ranging from 6 to 23 Msun. The level of fragmentation is globally higher than in the turbulence regulated, monolithic collapse scenario, but is not as high as expected in a pure gravo-turbulent scenario where the distribution of mass is dominated by low-mass protostars/stars. Here, the fractions of the total core masses in the high-mass fragments are reaching values as high as 28, 44, and 100 % in CygX-N12, CygX-N53, and CygX-N63, respectively, much higher than what an IMF-like mass distribution would predict. The increase of the fragmentation efficiency as a function of density in the cores is proposed to be due to the increasing importance of self-gravity leading to gravitational collapse at the scale of the dense cores. At the same time, the cores tend to fragment into a few massive protostars within their central regions. We are therefore probably witnessing here the primordial mass segregation of clusters in formation.Comment: 14 pages, 16 figures, submitted for publication in A&

The earliest phases of high-mass star formation: a 3 square degree millimeter continuum mapping of Cygnus X

We have made an extensive 1.2mm continuum mosaicing study of the Cygnus X molecular cloud complex using the MAMBO cameras at the IRAM 30 m telescope. We then compared our mm maps with mid-IR images, and have made SiO(2-1) follow-up observations of the best candidate progenitors of high-mass stars. Our complete study of Cygnus X provides, for the first time, an unbiased census of massive young stellar objects. We discover 129 massive dense cores, among which 42 are probable precursors of high-mass stars. Our study qualifies 17 cores as good candidates for hosting massive IR-quiet protostars, while up to 25 cores potentially host high-luminosity IR protostars. We fail to discover the high-mass analogs of pre-stellar dense cores in CygnusX, but find several massive starless clumps that might be gravitationally bound. Since our sample is derived from a single molecular complex and covers every embedded phase of high-mass star formation, it gives the first statistical estimates of their lifetime. In contrast to what is found for low-mass class 0 and class I phases, the IR-quiet protostellar phase of high-mass stars may last as long as their better-known high-luminosity IR phase. The statistical lifetimes of high-mass protostars and pre-stellar cores (~ 3 x 10^4 yr and < 10^3 yr) in Cygnus X are one and two order(s) of magnitude smaller, respectively, than what is found in nearby, low-mass star-forming regions. We therefore propose that high-mass pre-stellar and protostellar cores are in a highly dynamic state, as expected in a molecular cloud where turbulent processes dominate.Comment: 32 pages, 62 figures to be published in Astronomy & Astrophysics journa