9681382
A Dialectic Approach to Problem-Solving
We analyze the dynamics of problem-solving in a framework which captures two key features of that activity. The first feature is that problem-solving is a social game where a number of problem-solvers interact, rely on other agents to tackle parts of a problem, and regularly communicate the outcomes of their investigations. The second feature is that problem-solving requires a careful control over the set of hypotheses that might be needed at various stages of the investigation for the problem to be solved; more particularly, that any incorrect hypothesis be eventually refuted in the face of some evidence: all agents can expect such evidence to be brought to their knowledge whenever it holds. Our presentation uses a very general form of logic programs, viewed as sets of rules that can be activated and fire, depending on what a problem-solver is willing to explore, what a problem-solver is willing to hypothesize, and what a problem-solver knows about the problem to be solved in the form of data or background knowledge. 
 
Our framework supports two fundamental aspects of problem-solving. The first aspect is that no matter how the work is being distributed amongst agents, exactly the same knowledge is guaranteed to be discovered eventually. The second aspect is that any group of agents (with at one end, one agent being in charge of all rules and at another end, one agent being in charge of one and only one rule) might need to sometimes put forward some hypotheses to allow for the discovery of a particular piece of knowledge in finite time.
2402100
Input-Dependence in Function-Learning
In the standard literature on inductive inference, a learner sees as input the course of values of the function to be learned. In the present work, it is investigated how reasonable this choice is and how sensitive the model is with respect to variations like the overgraph or undergraph of the function. Several implications and separations are shown and for the basic notions, a complete picture is obtained. Furthermore, relations to oracles, additional information and teams are explored.
39139980
On Sufficient Conditions for Learnability of Logic Programs from Positive Data
Shinohara, Arimura, and Krishna Rao have shown learnability in the limit of minimal models of classes of logic programs from positive only data. In most cases, these results involve logic programs in which the "size" of the head yields a bound on the size of the body literals. However, when local variables are present, such a bound on body literal size cannot directly be ensured. The above authors achieve such a restriction using technical notions like mode and linear inequalities. The present paper develops a conceptually clean framework where the behavior of local variables is controlled by nonlocal ones. It is shown that for certain classes of logic programs, learnablity from positive data is equivalent to limiting identification of bounds for the number of clauses and the number of local variables. This reduces the learning problem finding two integers. This cleaner framework generalizes all the known results and establishes learnability of new classes.
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.
37212285
Quantification over names and modalities
7592429
On the Convergence of Incremental Knowledge Base Construction
Ripple Down Rules is a practical methodology to build knowledge-based systems, which has proved successful in a wide range of commercial applications. However, little work has been done on its theoretical foundations. In this paper, we formalise the key features of the method. We present the process of building a correct knowledge base as a discovery scenario involving a user, an expert, and a system. The user provides data for classification. The expert helps the system to build its knowledge base incrementally, using the output of the latter in response to the last datum provided by the user. In case the system’s output is not satisfactory, the expert guides the system to improve its future performance while not affecting its ability to properly classify past data. We examine under which conditions the sequence of knowledge bases constructed by the system eventually converges to a knowledge base that faithfully represents the target classification function. Our results are in accordance with the observed behaviour of real-life systems.
692
Memory Aware High-Level Synthesis for Embedded Systems
We introduce a new approach to take into account the memory architecture and the memory mapping in the High- Level Synthesis of Real-Time embedded systems. We formalize the memory mapping as a set of constraints used in the scheduling step. We use a memory mapping file to include those memory constraints in our HLS tool GAUT. Our scheduling algorithm exhibits a relatively low complexity that permits to tackle complex designs in a reasonable time. Finally, we show how to explore, with the help of GAUT, a wide range of solutions, and to reach a good tradeoff between time, power-consumption, and area.
18045473
Low power design of an acoustic echo canceller Gmdf/spl alpha/ algorithm on dedicated VLSI architectures
The acoustic echo cancellation with adaptive filters is a computationally intensive problem that needs real time cost effective solutions for embedded systems. Low power optimized signal processing architectures are likely to provide such solutions in the future. In this paper, we present different real-time optimized architectures of the popular Gmdf/spl alpha/ algorithm, obtained by an HLS CAD tool providing trade-off-between area and power dissipation.
11623202
A memory aware behavioral synthesis tool for real-time VLSI circuits
We introduce a new approach to take into account the memory architecture and the memory mapping in the Behavioral Synthesis of Real-Time VLSI circuits. We formalize the memory mapping as a set of constraints for the thesis, 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 straints in our HLS tool GAUT. Our scheduling algorithm exhibits a relatively low complexity that permits to tackle complex designs in a reasonable time. Several experiments are performed to demonstrate the efficiency of our method, and to compare GAUT with an industrial behavioral synthesis tool. We finally show how to explore, with the help of GAUT, a wide range of solutions, and to reach a good tradeoffs between time, power-consumption, and area.
16535802
Power Consumption Modeling and Characterization of the TI C6201
This new approach characterizes power dissipation on complex dsps. its processor model relies on an initial functional-level power analysis of the target processor together with a characterization that qualifies the more significant architectural and algorithmic parameters for power dissipation. these parameters come from a simple profiling of the assembly code. This functional model accounts for deeply pipelined, superscalar, and hierarchical memory architectures.
34309839
Design of a flexible 2-D discrete wavelet transform IP core for JPEG2000 image coding in embedded imaging systems
The increasingly demanding requirements of multimedia applications have led to the definition of complex image and video coding standards such as JPEG2000 and MPEG4. Implementation of image or video encoders or decoders on mobile device requires high integration densities together with ability for "real-time" (on-the-fly) data processing. Today, the electronic system design community is mainly concerned with defining efficient System-on-a-Chip (SoC) design methodologies in order to benefit from the high integration capabilities of current application-specific integrated circuit and field-programmable gate array technologies on the one hand, and manage the increasing algorithmic complexity of applications on the other hand. Intellectual property (IP) reuse is considered as the key to speed up the system design and verification flow and make it more reliable.In this context, we have introduced a novel methodology for VLSI implementation of computation-intensive algorithms targeting digital signal processing applications. Our methodology combines IP reuse and high-level synthesis (HLS) and introduces the notion of "Behavioral IP". This approach aims at leveraging IP re-usability through functional and architectural flexibility based on: (1) modeling a component's behavior at a high abstraction level and (2) benefiting from HLS tools for architectural exploration and hardware generation.In this paper, we illustrate our methodology in the case of a 2-D discrete wavelet transform IP core for JPEG2000 image compression. We describe the successive views of the component throughout the design flow, from the application level down to the architectural level. We also provide synthesis results showing the variety of dedicated architectures that can be generated depending on user-defined functional-level, system-level and architectural-level requirements. We compare the performance and re-usability of the set of obtained architectures versus hand-crafted RTL specifications.