Hierarchical Decomposition of Nonlinear Dynamics and Control for System Identification and Policy Distillation

The control of nonlinear dynamical systems remains a major challenge for autonomous agents. Current trends in reinforcement learning (RL) focus on complex representations of dynamics and policies, which have yielded impressive results in solving a variety of hard control tasks. However, this new sophistication and extremely over-parameterized models have come with the cost of an overall reduction in our ability to interpret the resulting policies. In this paper, we take inspiration from the control community and apply the principles of hybrid switching systems in order to break down complex dynamics into simpler components. We exploit the rich representational power of probabilistic graphical models and derive an expectation-maximization (EM) algorithm for learning a sequence model to capture the temporal structure of the data and automatically decompose nonlinear dynamics into stochastic switching linear dynamical systems. Moreover, we show how this framework of switching models enables extracting hierarchies of Markovian and auto-regressive locally linear controllers from nonlinear experts in an imitation learning scenario.Comment: 2nd Annual Conference on Learning for Dynamics and Contro

Three-dimensional surface grid generation for calculation of thermal radiation shape factors

A technique is described to generate three dimensional surface grids suitable for calculating shape factors for thermal radiative heat transfer. The surface under consideration is approximated by finite triangular elements generated in a special manner. The grid is generated by dividing the surface into a two dimensional array of nodes. Each node is defined by its coordinates. Each set of four adjacent nodes is used to construct two triangular elements. Each triangular element is characterized by the vector representation of its vertices. Vector algebra is used to calculate all desired geometric properties of grid elements. The properties are used to determine the shape factor between the element and an area element in space. The grid generation can be graphically displayed using any software with three dimensional features. DISSPLA was used to view the grids

Defensive alliance polynomial

We introduce a new bivariate polynomial which we call the defensive alliance polynomial and denote it by da(G; x, y). It is a generalization of the alliance polynomial [Carballosa et al., 2014] and the strong alliance polynomial [Carballosa et al., 2016]. We show the relation between da(G; x, y) and the alliance, the strong alliance and the induced connected subgraph [Tittmann et al., 2011] polynomials. Then, we investigate information encoded in da(G; x, y) about G. We discuss the defensive alliance polynomial for the path graphs, the cycle graphs, the star graphs, the double star graphs, the complete graphs, the complete bipartite graphs, the regular graphs, the wheel graphs, the open wheel graphs, the friendship graphs, the triangular book graphs and the quadrilateral book graphs. Also, we prove that the above classes of graphs are characterized by its defensive alliance polynomial. A relation between induced subgraphs with order three and both subgraphs with order three and size three and two respectively, is proved to characterize the complete bipartite graphs. Finally, we present the defensive alliance polynomial of the graph formed by attaching a vertex to a complete graph. We show two pairs of graphs which are not characterized by the alliance polynomial but characterized by the defensive alliance polynomial

A syntactic language model based on incremental CCG parsing

Syntactically-enriched language models (parsers) constitute a promising component in applications such as machine translation and speech-recognition. To maintain a useful level of accuracy, existing parsers are non-incremental and must span a combinatorially growing space of possible structures as every input word is processed. This prohibits their incorporation into standard linear-time decoders. In this paper, we present an incremental, linear-time dependency parser based on Combinatory Categorial Grammar (CCG) and classification techniques. We devise a deterministic transform of CCGbank canonical derivations into incremental ones, and train our parser on this data. We discover that a cascaded, incremental version provides an appealing balance between efficiency and accuracy

Amorphous Placement and Retrieval of Sensory Data in Sparse Mobile Ad-Hoc Networks

Abstract—Personal communication devices are increasingly being equipped with sensors that are able to passively collect information from their surroundings – information that could be stored in fairly small local caches. We envision a system in which users of such devices use their collective sensing, storage, and communication resources to query the state of (possibly remote) neighborhoods. The goal of such a system is to achieve the highest query success ratio using the least communication overhead (power). We show that the use of Data Centric Storage (DCS), or directed placement, is a viable approach for achieving this goal, but only when the underlying network is well connected. Alternatively, we propose, amorphous placement, in which sensory samples are cached locally and informed exchanges of cached samples is used to diffuse the sensory data throughout the whole network. In handling queries, the local cache is searched first for potential answers. If unsuccessful, the query is forwarded to one or more direct neighbors for answers. This technique leverages node mobility and caching capabilities to avoid the multi-hop communication overhead of directed placement. Using a simplified mobility model, we provide analytical lower and upper bounds on the ability of amorphous placement to achieve uniform field coverage in one and two dimensions. We show that combining informed shuffling of cached samples upon an encounter between two nodes, with the querying of direct neighbors could lead to significant performance improvements. For instance, under realistic mobility models, our simulation experiments show that amorphous placement achieves 10% to 40% better query answering ratio at a 25% to 35% savings in consumed power over directed placement.National Science Foundation (CNS Cybertrust 0524477, CNS NeTS 0520166, CNS ITR 0205294, EIA RI 0202067

A syntactified direct translation model with linear-time decoding

Recent syntactic extensions of statistical translation models work with a synchronous context-free or tree-substitution grammar extracted from an automatically parsed parallel corpus. The decoders accompanying these extensions typically exceed quadratic time complexity. This paper extends the Direct Translation Model 2 (DTM2) with syntax while maintaining linear-time decoding. We employ a linear-time parsing algorithm based on an eager, incremental interpretation of Combinatory Categorial Grammar (CCG). As every input word is processed, the local parsing decisions resolve ambiguity eagerly, by selecting a single supertag–operator pair for extending the dependency parse incrementally. Alongside translation features extracted from the derived parse tree, we explore syntactic features extracted from the incremental derivation process. Our empirical experiments show that our model significantly outperforms the state-of-the art DTM2 system

MaTrEx: the DCU machine translation system for IWSLT 2007

In this paper, we give a description of the machine translation system developed at DCU that was used for our second participation in the evaluation campaign of the International Workshop on Spoken Language Translation (IWSLT 2007). In this participation, we focus on some new methods to improve system quality. Specifically, we try our word packing technique for different language pairs, we smooth our translation tables with out-of-domain word translations for the Arabic–English and Chinese–English tasks in order to solve the high number of out of vocabulary items, and finally we deploy a translation-based model for case and punctuation restoration