in the number of features, and it implicitly finds correspondences based on the finest resolution histogram cell where a matched pair first appears. Since the kernel does not penalize the presence of extra features, it is robust to clutter. We show the kernel function is positive-definite, making it valid

The C programming language was devised in the early 1970s as a system implementation language for the nascent Unix operating system. Derived from the typeless language BCPL, it evolved a type structure; created on a tiny machine as a tool to improve a meager programming environment, it has become one of the dominant languages of today. This paper studies its evolution.

this paper we first discuss the wire metrics of interest and examine them in a contemporary 0.25m process. We then discuss technology scaling over the next several generations, from SIA and other predictions, and how our wire metrics trend over that time. We will examine the delay and bandwidth limitations of both long global wires and short local wires and discuss architectural design techniques that help us avoid the limitations of scaled wires.

In this paper we describe T-MAC, a contention-based Medium Access Control protocol for wireless sensor networks. Applications for these networks have some characteristics (low message rate, insensitivity to latency) that can be exploited to reduce energy consumption by introducing an active/sleep duty cycle. To handle load variations in time and location T-MAC introduces an adaptive duty cycle in a novel way: by dynamically ending the active part of it. This reduces the amount of energy wasted on idle listening, in which nodes wait for potentially incoming messages, while still maintaining a reasonable throughput. We discuss

An important question in neuroevolution is how to gain an advantage from evolving neural network topologies along with weights. We present a method, NeuroEvolution of Augmenting Topologies (NEAT), which outperforms the best fixed-topology method on a challenging benchmark reinforcement learning task. We claim that the increased efficiency is due to (1) employing a principled method of crossover of different topologies, (2) protecting structural innovation using speciation, and (3) incrementally growing from minimal structure. We test this claim through a series of ablation studies that demonstrate that each component is necessary to the system as a whole and to each other. What results is significantly faster learning. NEAT is also an important contribution to GAs because it shows how it is possible for evolution to both optimize and complexify solutions simultaneously, offering the possibility of evolving increasingly complex solutions over generations, and strengthening the analogy with biological evolution.

This book presents a unified treatment of many different kinds of planning algorithms. The subject lies at the crossroads between robotics, control theory, artificial intelligence, algorithms, and computer graphics. The particular subjects covered include motion planning, discrete planning, planning under uncertainty, sensor-based planning, visibility, decision-theoretic planning, game theory, information spaces, reinforcement learning, nonlinear systems, trajectory planning, nonholonomic planning, and kinodynamic planning.

We discuss the design of an acquisitional query processor for data collection in sensor networks. Acquisitional issues are those that pertain to where, when, and how often data is physically acquired (sampled) and delivered to query processing operators. By focusing on the locations and costs of acquiring data, we are able to significantly reduce power consumption over traditional passive systems that assume the a priori existence of data. We discuss simple extensions to SQL for controlling data acquisition, and show how acquisitional issues influence query optimization, dissemination, and execution. We evaluate these issues in the context of TinyDB, a distributed query processor for smart sensor devices, and show how acquisitional techniques can provide significant reductions in power consumption on our sensor devices. Categories and Subject Descriptors: H.2.3 [Database Management]: Languages—Query languages; H.2.4 [Database Management]: Systems—Distributed databases; query processing

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Mobile Ad Hoc Networks (MANETs) provide rapidly deployable and self-configuring network capacity required in many critical applications, e.g., battlefields, disaster relief and wide area sensing. In this paper we study the problem of efficient data delivery in sparse MANETs where network partitions can last for a significant period. Previous approaches rely on the use of either long range communication which leads to rapid draining of nodes ’ limited batteries, or existing node mobility which results in low data delivery rates and large delays. In this paper, we describe a Message Ferrying (MF) approach to address the problem. MF is a mobility-assisted approach which utilizes a set of special mobile nodes called message ferries (or ferries for short) to provide communication service for nodes in the deployment area. The main idea behind the MF approach is to introduce non-randomness in the movement of nodes and exploit such non-randomness to help deliver data. We study two variations of MF, depending on whether ferries or nodes initiate proactive movement. The MF design exploits mobility to improve data delivery performance and reduce energy consumption in nodes. We evaluate the performance of MF via extensive ns simulations which confirm the MF approach is efficient in both data delivery and energy consumption under a variety of network conditions.