Modelling the student in Pitagora 2.0

With the aim to individualise human-computer interaction, an Intelligent Tutoring System (ITS) has to keep track of what and how the student has learned. Hence, it is necessary to maintain a Student Model (SM) dealing with complex knowledge representation, such as incomplete and inconsistent knowledge and belief revision. With this in view, the main objective of this paper is to present and discuss the student modelling approach we have adopted to implement Pitagora 2.0, an ITS based on a co-operative learning model, and designed to support teaching-learning activities in a Euclidean Geometry context. In particular, this approach has led us to develop two distinct modules that cooperate to implement the SM of Pitagora 2.0. The first module resembles a classical student model, in the sense that it maintains a representation of the current student knowledge level, which can be used by the teacher in order to tune its teaching strategies to the specific student needs. In addition, our system contains a second module that implements a virtual partner, called companion. This module consists of a computational model of an average student which cooperates with the student during the learning process. The above mentioned module calls for the use of machine learning algorithms that allow the companion to improve in parallel with the real student. Computational results obtained when testing this module in simulation experiments are also presented.     

The CAM-Brain Machine (CBM): An FPGA Based Tool for Evolving a 75 Million Neuron Artificial Brain to Control a Lifesized Kitten Robot

This article introduces the CAM-Brain Machine (CBM), an FPGA based piece of hardware which implements a genetic algorithm (GA) to evolve a cellular automata (CA) based neural network circuit module, of approximately 1,000 neurons, in about a second, i.e., a complete run of a GA, with 10,000s of circuit growths and performance evaluations. Up to 65,000 of these modules, each of which is evolved with a humanly specified function, can be downloaded into a large RAM space, and interconnected according to humanly specified artificial brain architectures. This RAM, containing an artificial brain with up to 75 million neurons, is then updated by the CBM at a rate of 130 billion CA cells per second. Such speeds should enable real time control of robots and hopefully the birth of a new research field that we call brain building. The first such artificial brain, to be built in 2000 and beyond, will be used to control the behaviors of a life sized robotkitten called Robokitty.     

Data Buffering and Allocation in Mapping Generalized Template Matching on Reconfigurable Systems

Image processing algorithms for 2D digital filtering, morphologic operations, motion estimation, and template matching involve massively parallel computations that can benefit from using reconfigurable systems with massive field programmable gate array (FPGA) hardware resources. In addition, each algorithm can be considered a special case of a generalized template matching (GTM) operation. Application performance on reconfigurable computer systems is often limited by the bandwidth to host or off chip memory. This paper describes the GTM operation and characterizes the data allocation and buffering strategies for the GTM operation on reconfigurable computers. Several mechanisms that support different levels of parallelism are proposed and summarized in the paper. Finally, the implementation of an infrared automatic target recognition application on two commercial FPGA boards is used to demonstrate the various design options with different data allocation and buffering mechanisms and the pruning of the design space based on the FPGA area and memory constraints.     

Unitary immersions of nonlinear systems

In this paper, we define what we call a unitary immersion of a nonlinear system. We observe that, for classical Hamiltonian systems, this notion contains, in some sense, the concept of quantization. We restrict our attention to degree-zero unitary immersions, where all observation functions must be represented by operators of the type multiplication by a function. We show that the problem of classifying such degree-zero unitary immersions of a given nonlinear system is not obvious. In some cases, we solve this problem.Chargé de Recherche au CNRS.Maître de Conférences.     

Robust algorithms for packet routing in a mesh

This paper considers the problem of permutation packet routing on a n×n mesh-connected array of processors. Each node in the array is assumed to be independently faulty with a probability bounded above by a valuep. This paper gives a routing algorithm which, ifp 0.29, will with very high probability route every packet that can be routed inO(n logn) steps with queue lengths that areO(log² n). Extensions to higher-dimensional meshes are given.     

A variotherm mold for micro metal injection molding

In this paper, a variotherm mold was designed and fabricated for the production of 316L stainless steel microstructures by micro metal injection molding (MIM). The variotherm mold incorporated a rapid heating/cooling system, vacuum unit, hot sprue and cavity pressure transducer. The design of the variotherm mold and the process cycle of MIM using the variotherm mold were described. Experiments were conducted to evaluate the molded microstructures produced using variotherm mold and conventional mold. The experiments showed that microstructures of higher aspect ratio such as 60 m × height 191 m and 40 m × height 174 m microstructures could be injection molded with complete filling and demolded successfully using the variotherm mold. Molded microstructures with dimensions of 60 m × height 191 m were successfully debound and sintered without visual defects.     

The informed neuron: Issues in the use of information theory in the behavioral sciences

The concept of information is virtually ubiquitous in contemporary cognitive science. It is claimed to be processed (in cognitivist theories of perception and comprehension), stored (in cognitivist theories of memory and recognition), and otherwise manipulated and transformed by the human central nervous system. Fred Dretske's extensive philosophical defense of a theory of informational content (semantic information) based upon the Shannon-Weaver formal theory of information is subjected to critical scrutiny. A major difficulty is identified in Dretske's equivocations in the use of the concept of a signal bearing informational content. Gibson's alternative conception of information (construed as analog by Dretske), while avoiding many of the problems located in the conventional use of signal, raises different but equally serious questions. It is proposed that, taken literally, the human CNS does not extract or process information at all; rather, whatever information is construed as locatable in the CNS is information only for an observer-theorist and only for certain purposes.Blood courses through our veins, andinformation through our central nervous system.— A Neuropsychology Textbook.     

AI & Society and society

This article looks at the broadest implications of public acceptance of AI. A distinction is drawn between conscious belief in a technology, and organic belief where the technology is incorporated into an unconscious world model. The extent to which we feel threatened by AI's apparent denial of spirit is considered, along with a discussion of how people react to this threat. It is proposed that organic acceptance of AI models would lead to a rebirth of popular spiritual concepts as paradoxical as the New Age ideas that have their roots in the theories of physics. Finally the relevance of this speculation is discussed in terms of how it could impinge upon public acceptability of AI technology.     

Feature construction with Inductive Logic Programming: A Study of Quantitative Predictions of Biological Activity Aided by Structural Attributes

Recently, computer programs developed within the field of Inductive Logic Programming (ILP) have received some attention for their ability to construct restricted first-order logic solutions using problem-specific background knowledge. Prominent applications of such programs have been concerned with determining structure-activity relationships in the areas of molecular biology and chemistry. Typically the task here is to predict the activity of a compound (for example, toxicity), from its chemical structure. A summary of the research in the area is: (a) ILP programs have largely been restricted to qualitative predictions of activity (high, low etc.); (b) When appropriate attributes are available, ILP programs have equivalent predictivity to standard quantitative analysis techniques like linear regression. However ILP programs usually perform better when such attributes are unavailable; and (c) By using structural information as background knowledge, an ILP program can provide comprehensible explanations for biological activity. This paper examines the use of ILP programs as a method of discovering new attributes. These attributes could then be used by methods like linear regression, thus allowing for quantitative predictions while retaining the ability to use structural information as background knowledge. Using structure-activity tasks as a test-bed, the utility of ILP programs in constructing new features was evaluated by examining the prediction of biological activity using linear regression, with and without the aid of ILP learnt logical attributes. In three out of the five data sets examined the addition of ILP attributes produced statistically better results. In addition six important structural features that have escaped the attention of the expert chemists were discovered. The method used here to construct new attributes is not specific to the problem of predicting biological activity, and the results obtained suggest a wider role for ILP programs in aiding the process of scientific discovery.     

Specification and automatic verification of self-timed queues

Speed-independent circuit design is of increasing interest because of global timing problems in VLSI. Unfortunately, speed-independent design is very subtle. We propose the use of statemachine verification tools to ameliorate this problem. This article illustrates issues in the modeling, specification, and verification of speed-independent circuits through consideration of self-timed queues. User-level specifications are given as Petri nets, which are translated into trace structures for automatic processing. Three different implementations of queues are considered: a chain of queue cells, two parallel chains, and a circular buffer example using a separate RAM.