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Proceedings of the 12Th International Conference on Characteristics That Make One Method More Efficient Space Operations, Spaceops

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Proceedings of the 12Th International Conference on Characteristics That Make One Method More Efficient Space Operations, Spaceops The 26th International Conference ON Automated Planning AND Scheduling June 12-17, 2016. London, UK DoctorAL Consortium Dissertation AbstrACTS The DoctorAL Consortium BRINGS TOGETHER JUNIOR AND EXPERIENCED RESEARCHERS IN planning, SCHEDULING AND RELATED AREAS FROM ACROSS THE globe, IN PARTICULAR THOSE STUDYING FOR A DoctorAL degree. It PROVIDES A FORUM FOR NETWORKING WITH THE ICAPS COMMUNITY IN AN informal, SOCIAL setting. The DoctorAL Consortium WILL BE HELD AS A FULL DAY WORKSHOP ON June 12th, 2016. The PROGRAM INCLUDES AN INVITED TALK ON RESEARCH SKILLS AND CAREER DEVelopment, THE OPPORTUNITY FOR PARTICIPANT TO GIVE A SHORT presentation, AND A POSTER SESSION DURING THE MAIN conference. DC Chairs: • PETER Gregory (UnivERSITY OF Teeside, UK) • LEE McCluskEY (UnivERSITY OF Huddersfield, UK) • Fabio Mercorio (UnivERSITY OF Milan-Bicocca, Italy) AbstrACTS 1 Heuristic Search AND Applications ......................................... 3 Automated Planning AND Scheduling E0 Constellations’ OperATIONS USING Ant ColonY Optimization ... 4 Evridiki Ntagiou SolvER PARAMTER TUNING AND Runtime Predictions OF FleXIBLE Hybrid Mathematical MODELS ......... 10 Michael Barry Constructing Heuristics FOR PDDL+ Planning Domains ............................... 15 Wiktor PiotrOWSKI Risk-SensitivE Planning WITH Dynamic Uncertainty ................................. 21 Liana Marinescu 2 Multi Agent Planning & Plan ExECUTION ...................................... 27 A Distributed Online Multi-Agent Planning System ................................. 28 Rafael CarDOSO IntegrATING Planning AND Recognition TO Close THE InterACTION LOOP ....................... 34 Rick FREEDMAN Distributed Privacy-preserving Multi-agent Planning ................................ 39 AndrEA Bonisoli Planning WITH Concurrent ExECUTION .......................................... 44 Bence Cserna 3 TEMPORAL Planning ................................................... 47 MixED Discrete-Continuous Planning WITH CompleX BehaVIORS .......................... 48 Enrique FERNANDEZ Golzalez Planning WITH FleXIBLE Timelines IN THE Real WORLD ................................. 54 AlessandrO Umbrico POPCorn: Planning WITH ConstrAINED Real Numerics ................................ 60 EmrE SavAS Planning WITH PDDL3.0 Preferences BY Compilation INTO STRIPS WITH Action Costs ............. 66 FRANCESCO PERCASSI Planning Under Uncertainty WITH TEMPORALLY Extended Goals .......................... 71 Alberto Camacho TEMPORAL Inference In FORWARD Search TEMPORAL Planning ............................. 73 ATIF TALUKDAR 4 Planning AND Scheduling ............................................... 79 1 TASK Scheduling AND TRAJECTORY GenerATION OF Multiple Intelligent VEHICLES .................. 80 Jennifer David Decoupled State Space Search .............................................. 83 Daniel Gnad HierARCHICAL TASK Model WITH AlternativES FOR Predictive-reactivE Scheduling ................. 89 MarEK Vlk Numeric Planning ..................................................... 94 Johannes Aldinger Exploiting Search Space Structure IN Classical Planning: Analyses AND Algorithms .............. 97 Matasaru Asai SAT/SMT TECHNIQUES FOR PLANNING PROBLEMS ...................................... 102 Joan Espasa ArxER 5 Planning UNDER Uncertainty AND Applications .................................. 106 Robotic CONTROL THROUGH model-free REINFORCEMENT LEARNING ........................... 107 Ludovic Hofer Exploiting Symmetries IN Sequential Decision Making UNDER Uncertainty ................... 109 Ankit Anand Recommending AND Planning TRIP ItinerARIES FOR Individual TRAVELLERS AND Groups OF TOURISTS ....... 115 KWAN Hui LIM Constructing Plan TREES FOR Simulated PENETRATION TESTING ............................ 121 Dorin ShmaryAHU Optimization Approaches TO Multi-robot Planning AND Scheduling ........................ 128 KYLE Booth 6 Knowledge Engineering AND Applications ..................................... 131 LEARNING Static ConstrAINTS FOR Domain Modeling FROM TRAINING Plans ...................... 132 Rabia Jilani Using GORE METHOD FOR Requirement Engineering OF Planning & Scheduling .................. 137 Javier Martinez Critical ConstrAINED Planning AND AN Application TO Network PENETRATION TESTING .............. 141 MarCEL Steinmetz Human-Robot Communication IN Automated Planning ............................... 145 Aleck MacNally Session 1 Heuristic Search AND Applications 3 Automated Planning and Scheduling ΕΟ Constellations’ Operations with Ant Colony Optimization Evridiki Vasileia Ntagiou Surrey Space Centre, University of Surrey Abstract The Earth observing satellites (EOSs) picture the Earth’s surface, in order to satisfy an assigned goal, In this work we are interested in Automating the which in our case will be the imaging of the Area of process of Planning and Scheduling the operations Interest (AoI). EOSs can acquire images, while of an Earth Observation constellation. To this moving on their usually low altitude orbits. The respect, we represent the problem with a directed acquired data will then need to be transmitted to the graph and use Ant Colony Optimization technique ground station. Until that is possible, the data are to find the optimal solution. In order to verify the stored in the limited on-board memory of the quality of the solution, we employ a dynamical satellites, limiting the images that can be acquired system. We check the scalability of the software before the downlink. system performing simulations. We discuss the next There is a wide interest for automating the P&S process in the EO field, emanating not only steps of this work which involve the coordination of from research organizations and universities [C. multiple spacecraft by means of stigmergy and the Iacopino et al], but also from commercial operators consideration of more than one objectives that need and agencies [S. A. Chien et al.]. The main benefit of to be optimized. autonomy in the planning & scheduling field is in being able to gain maximum value from the Motivation and Scope spacecraft by maximizing the use of on board resources and providing a greater level of The increasing interest in the design and responsiveness to sudden changes of priority, such development of space missions consisting of as when natural disasters strike. Automating the multiple coordinated spacecraft cannot be missed, in P&S process of an Earth Observation mission recent years. Ranging from low cost due to less involves optimization and coordination. It is a system reliability requirements, to giving man the combinatorial optimization problem that takes place ability to perform concurrent scientific observations, in an uncertain dynamic environment. The the advantages of using constellations of spacecraft development of an automated P & S system also have attracted the complete attention of the Space follows the needs of the upcoming missions. These community [T. A. Wagner et al.]. The Earth employ dozens of agile satellites, where a change of Observation market, in specific, is expected to grow attitude translates to a tilt of the imager. We consider at a rate of 16% per year over the next decade [N. agile EOSs that can be steered up to 45° off-nadir in Muscettola et al.]. The current trend is towards the roll axis. constellations consisting of many small satellites, An EO mission may have a single goal e.g. with an increasing number of start-up companies maximize the imaged area, and many constraints, aiming at launching such constellations of 20 e.g. resource or weather constraints. It could also hundreds or more mini-satellites. [G. Richardson et have multiple goals which are conflicting e.g. al.][E. Buchen] maximize the imaged area, while minimizing the The reduction of the satellites’ size and resource used, and again numerous constraints. In corresponding shrinking of their cost has allowed fact, the nature of the problem is such that it includes many end users to benefit from data coming from many constraints, when realistic scenarios are satellites. Since we are dealing with the cooperation studied. In most of the studies, a single-objective of numerous miniaturized satellites of simple optimization problem with numerous constraints is capabilities, which altogether form a very complex considered. This alone, means that our solution will system, the need to automate its management arises. be valid under several assumptions. In order to lift Traditional techniques have failed to cope with such those assumptions we try to decrease the number of a level of complexity. Planning and scheduling constraints and increase the number of goals. In this (P&S) the operations of an EO satellite is the process case, the P&S problem is a multi-objective of determining the time when the satellite performs optimization problem. In order for a mission to be specific arranged tasks, as the available resources, successful, the trade-off among the several images’ collection goals, weather condition and user objectives needs to be studied and a solution requirements evolve. More specifically, the P& S depending on the user requirements needs to be system is responsible for coordinating a produced. constellation’s satellites’ activities in order for the total value of the downlinked data to be maximized. 4 The main challenges that arise when requests, the weather conditions, e.t.c. Hence, the developing a software system that is meant to be challenge is to solve this problem in a way that these autonomous can be grouped in three main continuous environment
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