Robust Control of Uncertain Markov Decision Processes with Temporal Logic Specifications

We present a method for designing robust controllers for dynamical systems with linear temporal logic specifications. We abstract the original system by a finite Markov Decision Process (MDP) that has transition probabilities in a specified uncertainty set. A robust control policy for the MDP is generated that maximizes the worst-case probability of satisfying the specification over all transition probabilities in the uncertainty set. To do this, we use a procedure from probabilistic model checking to combine the system model with an automaton representing the specification. This new MDP is then transformed into an equivalent form that satisfies assumptions for stochastic shortest path dynamic programming. A robust version of dynamic programming allows us to solve for a $\epsilon$-suboptimal robust control policy with time complexity $O(\log 1/\epsilon)$ times that for the non-robust case. We then implement this control policy on the original dynamical system

Optimal Control of Mixed Logical Dynamical Systems with Long-Term Temporal Logic Specifications

We present a mathematical programming-based method for control of large a class of nonlinear systems subject to temporal logic task specifications. We consider Mixed Logical Dynamical (MLD) systems, which include linear hybrid automata, constrained linear systems, and piecewise affine systems. We specify tasks using a fragment of linear temporal logic (LTL) that allows both finite- and infinite-horizon properties to be specified, including tasks such as surveillance, periodic walking, repeated assembly, and environmental monitoring. Our method directly encodes an LTL formula as mixed-integer linear constraints on the MLD system, instead of computing a finite abstraction. This approach is efficient; for common tasks the formulation may use significantly fewer binary variables than related approaches. In simulation, we solve non-trivial temporal logic motion planning tasks for high-dimensional continuous systems using our approach

Sea ice as a source of sea salt aerosol to Greenland ice cores: a model-based study

Abstract. Growing evidence suggests that the sea ice surface is an important source of sea salt aerosol and this has significant implications for polar climate and atmospheric chemistry. It also offers the opportunity to use ice core sea salt records as proxies for past sea ice extent. To explore this possibility in the Arctic region, we use a chemical transport model to track the emission, transport and deposition of sea salt from both the open ocean and the sea ice, allowing us to assess the relative importance of each. Our results confirm the importance of sea ice sea salt (SISS) to the winter Arctic aerosol burden. For the first time, we explicitly simulate the sea salt concentrations of Greenland snow and find they match high resolution Greenland ice core records to within a factor of two. Our simulations suggest that SISS contributes to the winter maxima in sea salt characteristic of ice cores across Greenland. A north-south gradient in the contribution of SISS relative to open ocean sea salt (OOSS) exists across Greenland, with 50 % of sea salt being SISS at northern sites such as NEEM, while only 10 % of sea salt is SISS at southern locations such as ACT10C. Our model shows some skill at reproducing the inter-annual variability in sea salt concentrations for 1991–1999 AD, particularly at Summit where up to 62 % of the variability is explained. Future work will involve constraining what is driving this inter-annual variability and operating the model under different paleoclimatic conditions. This work was supported by a European Commission Horizon 2020 Marie Sklodowska-Curie Individual Fellowship (no. 658120, SEADOG) to Rachael H. Rhodes. Eric W. Wolff is supported by a Royal Society Professorship

CoverNet: Multimodal Behavior Prediction using Trajectory Sets

We present CoverNet, a new method for multimodal, probabilistic trajectory prediction for urban driving. Previous work has employed a variety of methods, including multimodal regression, occupancy maps, and 1-step stochastic policies. We instead frame the trajectory prediction problem as classification over a diverse set of trajectories. The size of this set remains manageable due to the limited number of distinct actions that can be taken over a reasonable prediction horizon. We structure the trajectory set to a) ensure a desired level of coverage of the state space, and b) eliminate physically impossible trajectories. By dynamically generating trajectory sets based on the agent's current state, we can further improve our method's efficiency. We demonstrate our approach on public, real-world self-driving datasets, and show that it outperforms state-of-the-art methods

The Growth Response of Two Diatom Species to Atmospheric Dust from the Last Glacial Maximum

Relief of iron (Fe) limitation in the surface Southern Ocean has been suggested as one driver of the regular glacial-interglacial cycles in atmospheric carbon dioxide (CO2). The proposed cause is enhanced deposition of Fe-bearing atmospheric dust to the oceans during glacial intervals, with consequent effects on export production and the carbon cycle. However, understanding the role of enhanced atmospheric Fe supply in biogeochemical cycles is limited by knowledge of the fluxes and ‘bioavailability’ of atmospheric Fe during glacial intervals. Here, we assess the effect of Fe fertilization by dust, dry-extracted from the Last Glacial Maximum portion of the EPICA Dome C Antarctic ice core, on the Antarctic diatom species Eucampia antarctica and Proboscia inermis. Both species showed strong but differing reactions to dust addition. E. antarctica increased cell number (3880 vs. 786 cells mL-1), chlorophyll a (51 vs. 3.9 μg mL-1) and particulate organic carbon (POC; 1.68 vs. 0.28 μg mL-1) production in response to dust compared to controls. P. inermis did not increase cell number in response to dust, but chlorophyll a and POC per cell both strongly increased compared to controls (39 vs. 15 and 2.13 vs. 0.95 ng cell-1 respectively). The net result of both responses was a greater production of POC and chlorophyll a, as well as decreased Si:C and Si:N incorporation ratios within cells. However, E, antarctica decreased silicate uptake for the same nitrate and carbon uptake, while P. inermis increased carbon and nitrate uptake for the same silicate uptake. This suggests that nutrient utilization changes in response to Fe addition could be driven by different underlying mechanisms between different diatom species. Enhanced supply of atmospheric dust to the surface ocean during glacial intervals could therefore have driven nutrient-utilization changes which could permit greater carbon fixation for lower silica utilization. Additionally, both species responded more strongly to lower amounts of direct Fe chloride addition than they did to dust, suggesting that not all the Fe released from dust was in a bioavailable form available for uptake by diatoms

Sea ice as a source of sea salt aerosol to Greenland ice cores: a model-based study

Growing evidence suggests that the sea ice surface is an important source of sea salt aerosol and this has significant implications for polar climate and atmospheric chemistry. It also suggests the potential to use ice core sea salt records as proxies for past sea ice extent. To explore this possibility in the Arctic region, we use a chemical transport model to track the emission, transport, and deposition of sea salt from both the open ocean and the sea ice, allowing us to assess the relative importance of each. Our results confirm the importance of sea ice sea salt (SISS) to the winter Arctic aerosol burden. For the first time, we explicitly simulate the sea salt concentrations of Greenland snow, achieving values within a factor of two of Greenland ice core records. Our simulations suggest that SISS contributes to the winter maxima in sea salt characteristic of ice cores across Greenland. However, a north–south gradient in the contribution of SISS relative to open-ocean sea salt (OOSS) exists across Greenland, with 50 % of winter sea salt being SISS at northern sites such as NEEM (77° N), while only 10 % of winter sea salt is SISS at southern locations such as ACT10C (66° N). Our model shows some skill at reproducing the inter-annual variability in sea salt concentrations for 1991–1999, particularly at Summit where up to 62 % of the variability is explained. Future work will involve constraining what is driving this inter-annual variability and operating the model under different palaeoclimatic conditions

Compositions of Dust and Sea Salts in the Dome C and Dome Fuji Ice Cores From Last Glacial Maximum to Early Holocene Based on Ice‐Sublimation and Single‐Particle Measurements

We analyzed the chemical compositions of dust and sea‐salt particles in the EPICA Dome C (EDC) ice core during 26–7 kyr BP using an ice‐sublimation technique and compared the results with existing data of the Dome Fuji (DF) ice core. Combined with ion concentration data, our data suggested similar sea‐salt fluxes in both cores and significantly lower dust flux in the EDC core. The differences in modal size and aspect ratio of dust particles between the two cores support the dominance of Patagonian source suggested by earlier works. The compositions of calcic dust showed major change at ~17 kyr BP, possibly reflecting a relative increase in dust transported via the upper troposphere. The calcium sulfate fraction was higher in the DF core than in the EDC core after ~17 kyr BP, suggesting that higher Patagonian dust contribution to the DF region. Abundant NaCl particles were found in the DF core in comparison with the EDC core from the LGM to early Holocene, possibly because of the high concentration of terrestrial dust in the DF core that reduced acid availability for sea‐salt modification. During the Holocene, the lower NaCl fraction and Cl−/Na+ ratio in the EDC core suggested that most Cl− was lost to the atmosphere from snow at Dome C, while it was preserved at Dome Fuji as NaCl and solid solution

WIRED: World Wide Web Interactive Remote Event Display

WIRED is a framework, written in Java, to build High Energy Physics event displays that can be used across the network. To guarantee portability across all platforms, WIRED is implemented in the Java language and uses the Swing user interface component set. It can be used as a stand-alone application or as an applet inside a WWW browser. The graphical user interface allows for multiple views and for multiple controls acting on those views. A detector tree control is available to toggle the visibility of parts of the events and detector geometry. XML (Extensible Markup Language), RMI (Remote Method Invocation) and CORBA loaders can be used to load event data as well as geometry data, and to connect to FORTRAN, C, C++ and Java reconstruction programs. Non-linear and non-Cartesian projections (e.g. fish-eye, rho-phi, rho-Z, phi-Z) provide special views to get a better understanding of events. WIRED has grown to be a framework in use and under development in several HEP experiments (ATLAS, CHORUS, DELPHI, LHCb, BaBar, D0 and ZEUS). WIRED event displays have also proven to be useful to explain High Energy Physics to the general public. Both CERN, in its travelling exhibition and MicroCosm, and RAL, during its open days, have displays set up