OpenRaiser/Intern-Atlas huggingface dataset:
Characterization of Information Channels for Asymptotic Mean Stationarity and Stochastic Stability of Non-stationary/Unstable Linear Systems
Venue: arXiv cs.IT 2012
Year: 2012

Stabilization of non-stationary linear systems over noisy communication channels is considered. Stochastically stable sources, and unstable but noise-free or bounded-noise systems have been extensively studied in information theory and control theory literature since 1970s, with a renewed interest in the past decade. There have also been studies on non-causal and causal coding of unstable/non-stationary linear Gaussian sources. In this paper, tight necessary and sufficient conditions for stochastic stabilizability of unstable (non-stationary) possibly multi-dimensional linear systems driven by Gaussian noise over discrete channels (possibly with memory and feedback) are presented. Stochastic stability notions include recurrence, asymptotic mean stationarity and sample path ergodicity, and the existence of finite second moments. Our constructive proof uses random-time state-dependent stochastic drift criteria for stabilization of Markov chains. For asymptotic mean stationarity (and thus sample path ergodicity), it is sufficient that the capacity of a channel is (strictly) greater than the sum of the logarithms of the unstable pole magnitudes for memoryless channels and a class of channels with memory. This condition is also necessary under a mild technical condition. Sufficient conditions for the existence of finite average second moments for such systems driven by unbounded noise are provided.
A Calculus for Generating Ground Explanations (Technical Report)
Venue: arXiv cs.LO 2012
Year: 2012

We present a modification of the superposition calculus that is meant to generate explanations why a set of clauses is satisfiable. This process is related to abductive reasoning, and the explanations generated are clauses constructed over so-called abductive constants. We prove the correctness and completeness of the calculus in the presence of redundancy elimination rules, and develop a sufficient condition guaranteeing its termination; this sufficient condition is then used to prove that all possible explanations can be generated infinite time for several classes of clause sets, including many of interest to the SMT community. We propose a procedure that generates a set of explanations that should be useful to a human user and conclude by suggesting several extensions to this novel approach.
Real-time jam-session support system
Venue: arXiv cs.HC 2012
Year: 2012

We propose a method for the problem of real time chord accompaniment of improvised music. Our implementation can learn an underlying structure of the musical performance and predict next chord. The system uses Hidden Markov Model to find the most probable chord sequence for the played melody and then a Variable Order Markov Model is used to a) learn the structure (if any) and b) predict next chord. We implemented our system in Java and MAX/Msp and compared and evaluated using objective (prediction accuracy) and subjective (questionnaire) evaluation methods.
Meditations on Quantified Constraint Satisfaction
Venue: arXiv cs.LO 2012
Year: 2012

The quantified constraint satisfaction problem (QCSP) is the problem of deciding, given a structure and a first-order prenex sentence whose quantifier-free part is the conjunction of atoms, whether or not the sentence holds on the structure. One obtains a family of problems by defining, for each structure B, the problem QCSP(B) to be the QCSP where the structure is fixed to be B. In this article, we offer a viewpoint on the research program of understanding the complexity of the problems QCSP(B) on finite structures. In particular, we propose and discuss a group of conjectures; throughout, we attempt to place the conjectures in relation to existing results and to emphasize open issues and potential research directions.
The Cooperative Cleaners Problem in Stochastic Dynamic Environments
Venue: arXiv cs.MA 2012
Year: 2012

In this paper we study the strengths and limitations of collaborative teams of simple agents. In particular, we discuss the efficient use of "ant robots" for covering a connected region on the $Z^{2}$ grid, whose area is unknown in advance and which expands stochastically. Specifically, we discuss the problem where an initial connected region of $S_0$ boundary tiles expand outward with probability $p$ at every time step. On this grid region a group of $k$ limited and simple agents operate, in order to clean the unmapped and dynamically expanding region. A preliminary version of this problem was discussed in [1],[2] involving a deterministic expansion of a region in the grid.In this work we extend the model and examine cases where the spread of the region is done stochastically, where each tile has some probability $p$ to expand, at every time step. For this extended model we obtain an analytic probabilistic lower bounds for the minimal number of agents and minimal time required to enable a collaborative coverage of the expanding region, regardless of the algorithm used and the robots' hardware and software specifications. In addition, we present an impossibility result, for a variety of regions that would be impossible to completely clean, regardless of the algorithm used. Finally, we validate the analytic bounds using extensive empirical computer simulation results.
Power Control in Multiuser Mulicarrier Wireless Data Networks
Venue: arXiv cs.IT 2012
Year: 2012

A game-theoretic model is presented to study the management of transmission power in a wireless data network. We propose a power game for a multiuser multicarrier setting where all the users are assumed to transmit at equal rate. At equilibrium, each user is shown to transmit over a single carrier, as in [Mehskati et al., 2006]. We derive the necessary conditions on the path gains when the Nash equilibrium point exists. We further prove the existence of the Nash equilibrium point using the concept of locally gross direction preserving map. A greedy algorithm is proposed and its correctness is established, where each user acts selfishly to achieve the Nash equilibrium point.
Shortest Path and Distance Queries on Road Networks: An Experimental Evaluation
Venue: arXiv cs.DB 2012
Year: 2012

Computing the shortest path between two given locations in a road network is an important problem that finds applications in various map services and commercial navigation products. The state-of-the-art solutions for the problem can be divided into two categories: spatial-coherence-based methods and vertex-importance-based approaches. The two categories of techniques, however, have not been compared systematically under the same experimental framework, as they were developed from two independent lines of research that do not refer to each other. This renders it difficult for a practitioner to decide which technique should be adopted for a specific application. Furthermore, the experimental evaluation of the existing techniques, as presented in previous work, falls short in several aspects. Some methods were tested only on small road networks with up to one hundred thousand vertices; some approaches were evaluated using distance queries (instead of shortest path queries), namely, queries that ask only for the length of the shortest path; a state-of-the-art technique was examined based on a faulty implementation that led to incorrect query results. To address the above issues, this paper presents a comprehensive comparison of the most advanced spatial-coherence-based and vertex-importance-based approaches. Using a variety of real road networks with up to twenty million vertices, we evaluated each technique in terms of its preprocessing time, space consumption, and query efficiency (for both shortest path and distance queries). Our experimental results reveal the characteristics of different techniques, based on which we provide guidelines on selecting appropriate methods for various scenarios.
Gaussian Processes for Sample Efficient Reinforcement Learning with RMAX-like Exploration
Venue: arXiv cs.AI 2012
Year: 2012

We present an implementation of model-based online reinforcement learning (RL) for continuous domains with deterministic transitions that is specifically designed to achieve low sample complexity. To achieve low sample complexity, since the environment is unknown, an agent must intelligently balance exploration and exploitation, and must be able to rapidly generalize from observations. While in the past a number of related sample efficient RL algorithms have been proposed, to allow theoretical analysis, mainly model-learners with weak generalization capabilities were considered. Here, we separate function approximation in the model learner (which does require samples) from the interpolation in the planner (which does not require samples). For model-learning we apply Gaussian processes regression (GP) which is able to automatically adjust itself to the complexity of the problem (via Bayesian hyperparameter selection) and, in practice, often able to learn a highly accurate model from very little data. In addition, a GP provides a natural way to determine the uncertainty of its predictions, which allows us to implement the "optimism in the face of uncertainty" principle used to efficiently control exploration. Our method is evaluated on four common benchmark domains.
The Satisfiability Threshold for a Seemingly Intractable Random Constraint Satisfaction Problem
Venue: arXiv cs.DM 2012
Year: 2012

We determine the exact threshold of satisfiability for random instances of a particular NP-complete constraint satisfaction problem (CSP). This is the first random CSP model for which we have determined a precise linear satisfiability threshold, and for which random instances with density near that threshold appear to be computationally difficult. More formally, it is the first random CSP model for which the satisfiability threshold is known and which shares the following characteristics with random k-SAT for k >= 3. The problem is NP-complete, the satisfiability threshold occurs when there is a linear number of clauses, and a uniformly random instance with a linear number of clauses asymptotically almost surely has exponential resolution complexity.
On the Design of Large Scale Wireless Systems (with detailed proofs)
Venue: arXiv cs.IT 2012
Year: 2012

In this paper, we consider the downlink of large OFDMA-based networks and study their performance bounds as a function of the number of - transmitters $B$, users $K$, and resource-blocks $N$. Here, a resource block is a collection of subcarriers such that all such collections, that are disjoint have associated independently fading channels. In particular, we analyze the expected achievable sum-rate as a function of above variables and derive novel upper and lower bounds for a general spatial geometry of transmitters, a truncated path-loss model, and a variety of fading models. We establish the associated scaling laws for dense and extended networks, and propose design guidelines for the regulators to guarantee various QoS constraints and, at the same time, maximize revenue for the service providers. Thereafter, we develop a distributed resource allocation scheme that achieves the same sum-rate scaling as that of the proposed upper bound for a wide range of $K, B, N$. Based on it, we compare low-powered peer-to-peer networks to high-powered single-transmitter networks and give an additional design principle. Finally, we also show how our results can be extended to the scenario where each of the $B$ transmitters have $M (>1)$ co-located antennas.
Spatial MAC in MIMO Communications and its Application to Underlay Cognitive Radio
Venue: arXiv cs.IT 2012
Year: 2012

We propose a learning technique for MIMO secondary users (SU) to spatially coexist with Primary Users (PU). By learning the null space of the interference channel to the PU, the SU can utilize idle degrees of freedom that otherwise would be unused by the PU. This learning process does not require any handshake or explicit information exchange between the PU and the SU. The only requirement is that the PU broadcasts a periodic beacon that is a function of its noise plus interference power, through a low rate control channel. The learning process is based on energy measurements, independent of the transmission schemes of both the PU and SU, i.e. independent of their modulation, coding etc.. The proposed learning technique also provides a novel spatial division multiple access mechanism for equal-priority MIMO users sharing a common channel that highly increases the spectrum utilization compared to time based or frequency multiple access.
Critical Points and Gröbner Bases: the Unmixed Case
Venue: arXiv cs.SC 2012
Year: 2012

We consider the problem of computing critical points of the restriction of a polynomial map to an algebraic variety. This is of first importance since the global minimum of such a map is reached at a critical point. Thus, these points appear naturally in non-convex polynomial optimization which occurs in a wide range of scientific applications (control theory, chemistry, economics,...). Critical points also play a central role in recent algorithms of effective real algebraic geometry. Experimentally, it has been observed that Gröbner basis algorithms are efficient to compute such points. Therefore, recent software based on the so-called Critical Point Method are built on Gröbner bases engines. Let $f_1,..., f_p$ be polynomials in $ \Q[x_1,..., x_n]$ of degree $D$, $V\subset\C^n$ be their complex variety and $π_1$ be the projection map $(x_1,.., x_n)\mapsto x_1$. The critical points of the restriction of $π_1$ to $V$ are defined by the vanishing of $f_1,..., f_p$ and some maximal minors of the Jacobian matrix associated to $f_1,..., f_p$. Such a system is algebraically structured: the ideal it generates is the sum of a determinantal ideal and the ideal generated by $f_1,..., f_p$. We provide the first complexity estimates on the computation of Gröbner bases of such systems defining critical points. We prove that under genericity assumptions on $f_1,..., f_p$, the complexity is polynomial in the generic number of critical points, i.e. $D^p(D-1)^{n-p}{{n-1}\choose{p-1}}$. More particularly, in the quadratic case D=2, the complexity of such a Gröbner basis computation is polynomial in the number of variables $n$ and exponential in $p$. We also give experimental evidence supporting these theoretical results.
Protocol Coding through Reordering of User Resources, Part II: Practical Coding Strategies
Venue: arXiv cs.IT 2012
Year: 2012

We use the term protocol coding to denote the communication strategies in which information is encoded through the actions taken by a certain communication protocol. In this work we investigate strategies for protocol coding via combinatorial ordering of the labelled user resources (packets, channels) in an existing, primary system. This introduces a new, secondary communication channel in the existing system, which has been considered in the prior work exclusively in a steganographic context. Instead, we focus on the use of secondary channel for reliable communication with newly introduced secondary devices, that are low-complexity versions of the primary devices, capable only to decode the robustly encoded header information in the primary signals. In Part I of the work we have characterized the capacity of the secondary channel through information-theoretic analysis. In this paper we consider practical strategies for protocol coding inspired by the information-theoretic analysis. It turns out that the insights from Part I are instrumental for devising superior design of error-control codes. This is demonstrated by comparing the error performance to the "na"ıve" strategy which is presumably available without carrying out the analysis in Part I. These results are clearly outlining both the conceptual novelty behind the discussed concept of secondary channel as well as its practical applicability.
Generating a Performance Stochastic Model from UML Specifications
Venue: arXiv cs.SE 2012
Year: 2012

Since its initiation by Connie Smith, the process of Software Performance Engineering (SPE) is becoming a growing concern. The idea is to bring performance evaluation into the software design process. This suitable methodology allows software designers to determine the performance of software during design. Several approaches have been proposed to provide such techniques. Some of them propose to derive from a UML (Unified Modeling Language) model a performance model such as Stochastic Petri Net (SPN) or Stochastic process Algebra (SPA) models. Our work belongs to the same category. We propose to derive from a UML model a Stochastic Automata Network (SAN) in order to obtain performance predictions. Our approach is more flexible due to the SAN modularity and its high resemblance to UML' state-chart diagram.
The implications of embodiment for behavior and cognition: animal and robotic case studies
Venue: arXiv cs.AI 2012
Year: 2012

In this paper, we will argue that if we want to understand the function of the brain (or the control in the case of robots), we must understand how the brain is embedded into the physical system, and how the organism interacts with the real world. While embodiment has often been used in its trivial meaning, i.e. 'intelligence requires a body', the concept has deeper and more important implications, concerned with the relation between physical and information (neural, control) processes. A number of case studies are presented to illustrate the concept. These involve animals and robots and are concentrated around locomotion, grasping, and visual perception. A theoretical scheme that can be used to embed the diverse case studies will be presented. Finally, we will establish a link between the low-level sensory-motor processes and cognition. We will present an embodied view on categorization, and propose the concepts of 'body schema' and 'forward models' as a natural extension of the embodied approach toward first representations.
Exact Scalar Minimum Storage Coordinated Regenerating Codes
Venue: arXiv cs.IT 2012
Year: 2012

We study the exact and optimal repair of multiple failures in codes for distributed storage. More particularly, we examine the use of interference alignment to build exact scalar minimum storage coordinated regenerating codes (MSCR). We show that it is possible to build codes for the case of k = 2 and d > k by aligning interferences independently but that this technique cannot be applied as soon as k > 2 and d > k. Our results also apply to adaptive regenerating codes.
Comparing Background Subtraction Algorithms and Method of Car Counting
Venue: arXiv cs.CV 2012
Year: 2012

In this paper, we compare various image background subtraction algorithms with the ground truth of cars counted. We have given a sample of thousand images, which are the snap shots of current traffic as records at various intersections and highways. We have also counted an approximate number of cars that are visible in these images. In order to ascertain the accuracy of algorithms to be used for the processing of million images, we compare them on many metrics that includes (i) Scalability (ii) Accuracy (iii) Processing time.
Token-DCF: An Opportunistic MAC protocol for Wireless Networks
Venue: arXiv cs.NI 2012
Year: 2012

IEEE 802.11 DCF is the MAC protocol currently used in wireless LANs. 802.11 DCF is inefficient due to two types of overhead; channel idle time and collision time. This paper presents the design and performance evaluation of an efficient MAC protocol for wireless networks, called Token-DCF. Token-DCF decreases both idle time and collision time. In Token-DCF, each station keeps track of neighboring links' queue length by overhearing of transmitted packets on the wireless medium. The result is then used to assign privileges to the network stations. A privileged station does not follow the backoff mechanism and transmits immediately after the channel is sensed idle. Our simulation results show that Token-DCF can significantly improve channel utilization, system throughput and channel access delay over 802.11 DCF.
Influence of Topological Features on Spatially-Structured Evolutionary Algorithms Dynamics
Venue: arXiv cs.NE 2012
Year: 2012

In the last decades, complex networks theory significantly influenced other disciplines on the modeling of both static and dynamic aspects of systems observed in nature. This work aims to investigate the effects of networks' topological features on the dynamics of an evolutionary algorithm, considering in particular the ability to find a large number of optima on multi-modal problems. We introduce a novel spatially-structured evolutionary algorithm and we apply it on two combinatorial problems: ONEMAX and the multi-modal NMAX. Considering three different network models we investigate the relationships between their features, algorithm's convergence and its ability to find multiple optima (for the multi-modal problem). In order to perform a deeper analysis we investigate the introduction of weighted graphs with time-varying weights. The results show that networks with a large Average Path Length lead to an higher number of optima and a consequent slow exploration dynamics (i.e. low First Hitting Time). Furthermore, the introduction of weighted networks shows the possibility to tune algorithm's dynamics during its execution with the parameter related with weights' change. This work gives a first answer about the effects of various graph topologies on the diversity of evolutionary algorithms and it describes a simple but powerful algorithmic framework which allows to investigate many aspects of ssEAs dynamics.
Efficient Controller Synthesis for Consumption Games with Multiple Resource Types
Venue: arXiv cs.GT 2012
Year: 2012

We introduce consumption games, a model for discrete interactive system with multiple resources that are consumed or reloaded independently. More precisely, a consumption game is a finite-state graph where each transition is labeled by a vector of resource updates, where every update is a non-positive number or omega. The omega updates model the reloading of a given resource. Each vertex belongs either to player \Box or player \Diamond, where the aim of player \Box is to play so that the resources are never exhausted. We consider several natural algorithmic problems about consumption games, and show that although these problems are computationally hard in general, they are solvable in polynomial time for every fixed number of resource types (i.e., the dimension of the update vectors).
On the influence of intelligence in (social) intelligence testing environments
Venue: arXiv cs.AI 2012
Year: 2012

This paper analyses the influence of including agents of different degrees of intelligence in a multiagent system. The goal is to better understand how we can develop intelligence tests that can evaluate social intelligence. We analyse several reinforcement algorithms in several contexts of cooperation and competition. Our experimental setting is inspired by the recently developed Darwin-Wallace distribution.