37212285
Quantification over names and modalities
37385006
On a Syntactic Characterization of Classification with a Mind Change Bound
Most learning paradigms impose a particular syntax on the class of concepts to be learned; the chosen syntax can dramatically affect whether the class is learnable or not. For classification paradigms, where the task is to determine whether the underlying world does or does not have a particular property, how that property is represented has no implication on the power of a classifier that just outputs 1's or 0's. But is it possible to give a canonical syntactic representation of the class of concepts that are classifiable according to the particular criteria of a given paradigm? We provide a positive answer to this question for classification in the limit paradigms in a logical setting, with ordinal mind change bounds as a measure of complexity. The syntactic characterization that emerges enables to derive that if a possibly noncomputable classifier can perform the task assigned to it by the paradigm, then a computable classifier can also perform the same task. The syntactic characterization is strongly related to the difference hierarchy over the class of open sets of some topological space; this space is naturally defined from the class of possible worlds and possible data of the learning paradigm.
33304178
Scientific Discovery Based on Belief Revision
Scientific inquiry is represented as a process of rational hypothesis revision in the face of data. For the concept of rationality, we rely on the theory of belief dynamics as developed in [5, 9]. Among other things, it is shown that if belief states are left unclosed under deductive logic then scientific theories can be expanded in a uniform, consistent fashion that allows inquiry to proceed by any method of hypothesis revision based on "kernel" contraction. In contrast, if belief states are closed under logic, then no such expansion is possible. ?
38643151
Learning from Each Other
Since its inception, the field of machine learning has seen the advent of several learning paradigms, designed to frame the issues central to the learning activity, provide effective learning methods, and investigate the power and limitations inherent to the process of successful learning. In this article, we propose a formalization that underlies the key concepts of many such paradigms and discuss their relevance to scientific discovery, with the aim of assessing what scientists can expect from machines designed to assist them in their quest for the discovery of valid laws. We illustrate the formalization on several variations of a card game, and highlight the differences that paradigms impose on learners, as well as the assumptions they make on the nature of the learning process. We then use the formalization to describe a multi-agent interaction protocol, that has been inspired by these paradigms and that has been validated recently on some groups of agents. Finally, we propose extensions to this protocol.
33073441
Synthèse Comportementale Sous Contraintes de Communication et de Placement Mémoire pour les composants du TDSI
The design of complex Digital Signal Processing systems implies to minimize architectural cost and to maximize timing performances while taking into account communication and memory accesses constraints for the integration of dedicated hardware accelerator. Unfortunately, the traditional Matlab/ Simulink design flows gather not very flexible hardware blocs. In this paper, we present a methodology and a tool that permit the High-Level Synthesis of DSP applications, under both I/O timing and memory constraints. Based on formal models and a generic architecture, our tool GAUT helps the designer in finding a reasonable trade-off between the circuit's performance and its architectural complexity. The efficiency of our approach is demonstrated on the case study of a FFT algorithm.
1859636
Autonomous capture of a tumbling satellite
In this paper, we describe a framework for the autonomous capture and servicing of satellites. The work is based on laboratory experiments that illustrate the autonomy and remote-operation aspects. The satellite-capture problem is representative of most on-orbit robotic manipulation tasks where the environment is known and structured, but it is dynamic since the satellite to be captured is in free flight. Bandwidth limitations and communication dropouts dominate the quality of the communication link. The satellite-servicing scenario is implemented on a robotic test-bed in laboratory settings
205664504
Constrained algorithmic IP design for system-on-chip
In the system on chip design context, RTL design of complex digital signal processing coprocessors can be improved by using algorithmic description as input for the synthesis process. System integration, that is a major step in SoC design, requires taking into account communication and timing constraints to design and integrate dedicated hardware accelerator. In this paper, we propose a design flow based on formal models that allows high-level synthesis under input/output timing constraints of DSP algorithms. Based on a generic architecture, the presented method provides automatic generation of customized hardware components. We show the effectiveness of our approach in a case study of a maximum a posteriori (MAP) algorithm for turbo decoding.
17460903
A memory aware high level synthesis tool
We introduce a new approach to take into account the memory architecture and the memory mapping in high-level synthesis for data intensive applications. We formalize the memory mapping as a set of constraints for the synthesis, and defined a memory constraint graph and an accessibility criterion to be used in the scheduling step. We use a memory mapping file to include those memory constraints in our HLS tool GAUT. It is possible, with the help of GAUT, to explore a wide range of solutions, and to reach a good tradeoff between time, power-consumption, and area.
18182574
SoftExplorer: Estimation, Characterization, and Optimization of the Power and Energy Consumption at the Algorithmic Level
We present SoftExplorer, a tool to estimate and analyze the power and energy consumption of an algorithm from the C program. The consumption of every loop is analyzed, and the influence of the data mapping is characterized. Several models of processor are available, from the simple RISC ARM7 to the very complex VLIW DSP TI-C67. Cache misses, pipeline stalls, and internal / external memory accesses are taken into account. We show how to analyze and optimize the power and energy consumption, and how to choose a processor and its operating frequency, for a MPEG-1 decoder. We also explain how to find the best data mapping for a DSP application.