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Fluid Concepts and Creative Analogies: Computer Models of the Fundamental Mechanisms of Thought,
, 1995
"... Where does meaning enter the picture in artificial intelligence? How can we say that a machine possesses understanding? Where, and how, does such understanding happen? These are among the deepest and hardest questions faced by the field of artificial intelligence, which, as many claim, has not yield ..."
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Cited by 164 (2 self)
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Where does meaning enter the picture in artificial intelligence? How can we say that a machine possesses understanding? Where, and how, does such understanding happen? These are among the deepest and hardest questions faced by the field of artificial intelligence, which, as many claim, has not yielded much about them so far. But some results may be just around the corner to some, and that group includes Douglas Hofstadter and the Fluid Analogies Research Group. They have been developing some insightful analogy problem solving systems  based on the HEARSAY II speech understanding architecture  that really deserve notice. We review their recent book reporting on these systems here.
Threads and Input/Output in the Synthesis kernel
 In Proceedings of the 12th ACM Symposium on Operating Systems Principles
, 1989
"... The Synthesis operating system kernel combines several techniques to provide high performance, including kernel code synthesis, negrain scheduling, and optimistic synchronization. Kernel code synthesis reduces the execution path for frequently used kernel calls. Optimistic synchronization increases ..."
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Cited by 113 (13 self)
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The Synthesis operating system kernel combines several techniques to provide high performance, including kernel code synthesis, negrain scheduling, and optimistic synchronization. Kernel code synthesis reduces the execution path for frequently used kernel calls. Optimistic synchronization increases concurrency within the kernel. Their combination results in signi cant performance improvement over traditional operating system implementations. Using hardware and software emulating a SUN 3/160 running SUNOS, Synthesis achieves several times to several dozen times speedup for Unix kernel calls and context switch times of 21 microseconds or faster. 1
Abstraction and CounterexampleGuided Refinement in Model Checking of Hybrid Systems
, 2003
"... Hybrid dynamic systems include both continuous and discrete state variables. Properties of hybrid systems, which have an infinite state space, can often be verified using ordinary model checking together with a finitestate abstraction. Model checking can be inconclusive, however, in which case t ..."
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Cited by 53 (7 self)
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Hybrid dynamic systems include both continuous and discrete state variables. Properties of hybrid systems, which have an infinite state space, can often be verified using ordinary model checking together with a finitestate abstraction. Model checking can be inconclusive, however, in which case the abstraction must be refined. This paper presents a new procedure to perform this refinement operation for abstractions of hybrid systems. Following an approach originally developed for finitestate systems [11, 25], the refinement procedure constructs a new abstraction that eliminates a counterexample generated by the model checker. For hybrid systems, analysis of the counterexample requires the computation of sets of reachable states in the continuous state space. We show how such reachability computations with varying degrees of complexity can be used to refine hybrid system abstractions efficiently.
T2D: Generating Dialogues between Virtual Agents Automatically from Text
"... Abstract. The Text2Dialogue (T2D) system that we are developing allows digital content creators to generate attractive multimodal dialogues presented by two virtual agents—by simply providing textual information as input. We use Rhetorical Structure Theory (RST) to decompose text into segments and ..."
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Cited by 24 (22 self)
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Abstract. The Text2Dialogue (T2D) system that we are developing allows digital content creators to generate attractive multimodal dialogues presented by two virtual agents—by simply providing textual information as input. We use Rhetorical Structure Theory (RST) to decompose text into segments and to identify rhetorical discourse relations between them. These are then “acted out ” by two 3D agents using synthetic speech and appropriate conversational gestures. In this paper, we present version 1.0 of the T2D system and focus on the novel technique that it uses for mapping rhetorical relations to question–answer pairs, thus transforming (monological) text into a form that supports dialogues between virtual agents. 1
Gödel Machines: SelfReferential Universal Problem Solvers Making Provably Optimal SelfImprovements
, 2003
"... An old dream of computer scientists is to build an optimally efficient universal problem solver. We show how to solve arbitrary computational problems in an optimal fashion inspired by Kurt Gödel's celebrated selfreferential formulas (1931). Our Gödel machine's initial software includes ..."
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Cited by 19 (8 self)
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An old dream of computer scientists is to build an optimally efficient universal problem solver. We show how to solve arbitrary computational problems in an optimal fashion inspired by Kurt Gödel's celebrated selfreferential formulas (1931). Our Gödel machine's initial software includes an axiomatic description of: the Gödel machine's hardware, the problemspecific utility function (such as the expected future reward of a robot), known aspects of the environment, costs of actions and computations, and the initial software itself (this is possible without introducing circularity). It also includes a typically suboptimal initial problemsolving policy and an asymptotically optimal proof searcher searching the space of computable proof techniques  that is, programs whose outputs are proofs. Unlike previous approaches, the selfreferential Gödel machine will rewrite any part of its software, including axioms and proof searcher, as soon as it has found a proof that this will improve its future performance, given its typically limited computational resources. We show that selfrewrites are globally optimal  no local minima!since provably none of all the alternative rewrites and proofs (those that could be found by continuing the proof search) are worth waiting for.
Evolving Artificial Cell Signaling Networks using Molecular Classifier Systems
 in: 1st IEEE/ACM International Conference on BioInspired Models of Network, Information and Computing Systems (IEEE/ACM BIONETICS 2006), IEEE
, 2006
"... Abstract — Nature is a source of inspiration for computational techniques which have been successfully applied to a wide variety of complex application domains. In keeping with this we examine Cell Signaling Networks (CSN) which are chemical networks responsible for coordinating cell activities with ..."
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Cited by 16 (9 self)
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Abstract — Nature is a source of inspiration for computational techniques which have been successfully applied to a wide variety of complex application domains. In keeping with this we examine Cell Signaling Networks (CSN) which are chemical networks responsible for coordinating cell activities within their environment. Through evolution they have become highly efficient for governing critical control processes such as immunological responses, cell cycle control or homeostasis. Realising (and evolving) Artificial Cell Signaling Networks (ACSNs) may provide new computational paradigms for a variety of application areas. Our abstraction of Cell Signaling Networks focuses on four characteristic properties distinguished as follows: Computation, Evolution, Crosstalk and Robustness. These properties are also desirable for potential applications in the control systems, computation and signal processing field. These characteristics are used as a guide for the development of an ACSN evolutionary simulation platform. In this paper we present a novel evolutionary approach named Molecular Classifier System (MCS) to simulate such ACSNs. The MCS that we have designed is derived from Holland’s Learning Classifier System. The research we are currently involved in is part of the multi disciplinary European funded project, ESIGNET, with the central question of the study of the computational properties of CSNs by evolving them using methods from evolutionary computation, and to reapply this understanding in developing new ways to model and predict real CSNs. I.
On the behavior of a family of metaFibonacci sequences
 SIAM J. Discrete Math
, 2005
"... Abstract. A family of metaFibonacci sequences is defined by the kterm recursion k−1 � Ta,k(n): = Ta,k(n − i − a − Ta,k(n − i − 1)), n>a+ k, k ≥ 2, i=0 with initial conditions Ta,k(n) = 1 for 1 ≤ n ≤ a + k. Some partial results are obtained for a ≥ 0 and k>1. The case a = 0 and k odd is anal ..."
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Cited by 15 (6 self)
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Abstract. A family of metaFibonacci sequences is defined by the kterm recursion k−1 � Ta,k(n): = Ta,k(n − i − a − Ta,k(n − i − 1)), n>a+ k, k ≥ 2, i=0 with initial conditions Ta,k(n) = 1 for 1 ≤ n ≤ a + k. Some partial results are obtained for a ≥ 0 and k>1. The case a = 0 and k odd is analyzed in detail, giving a complete characterization of its structure and behavior, marking the first time that such a parametric family of metaFibonacci sequences has been solved. This behavior is considerably more complex than that of the more familiar Conolly sequence (a =0,k = 2). Various properties are derived: for example, a certain difference of summands turns out to consist of palindromic subsequences, and the mean values of the functions on these subsequences are computed. Conjectures are made concerning the still more complex behavior of a = 0 and even k>2.
Tuning & Simplifying Heuristical Optimization
, 2010
"... This thesis is about the tuning and simplification of blackbox (directsearch, derivativefree) optimization methods, which by definition do not use gradient information to guide their search for an optimum but merely need a fitness (cost, error, objective) measure for each candidate solution to th ..."
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Cited by 12 (0 self)
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This thesis is about the tuning and simplification of blackbox (directsearch, derivativefree) optimization methods, which by definition do not use gradient information to guide their search for an optimum but merely need a fitness (cost, error, objective) measure for each candidate solution to the optimization problem. Such optimization methods often have parameters that influence their behaviour and efficacy. A MetaOptimization technique is presented here for tuning the behavioural parameters of an optimization method by employing an additional layer of optimization. This is used in a number of experiments on two popular optimization methods, Differential Evolution and Particle Swarm Optimization, and unveils the true performance capabilities of an optimizer in different usage scenarios. It is found that stateoftheart optimizer variants with their supposedly adaptive behavioural parameters do not have a general and consistent performance advantage but are outperformed in several cases by simplified optimizers, if only the behavioural parameters are tuned properly.
G/SPLINES: A hybrid of friedman's multivariate adaptive regression splines (MARS) algorithm with Holland's genetic algorithm
 In Proceedings of the Fourth International Conference on Genetic Algorithms
, 1991
"... Adaptive Regression Splines (MARS) Al[[orithm with ..."
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Cited by 11 (0 self)
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Adaptive Regression Splines (MARS) Al[[orithm with