Results 11  20
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41
Flexible Optimization And Evolution Of Underwater Autonomous Agents
 New Directions in Rough Sets, Data Mining, and GranularSoft Computing, LNAI 1711
, 1999
"... The "Ocean SAmpling MObile Network" (SAMON) Project is a simulation testbed for Webbased interaction among oceanographers and simulation based design of Ocean Sampling missions. In this paper, the current implementation of SAMON is presented, along with a formal model based on process algebra. ..."
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Cited by 6 (4 self)
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The "Ocean SAmpling MObile Network" (SAMON) Project is a simulation testbed for Webbased interaction among oceanographers and simulation based design of Ocean Sampling missions. In this paper, the current implementation of SAMON is presented, along with a formal model based on process algebra. Flexible optimization handles planning, mobility, evolution, and learning. A generic behavior messagepassing language is developed for communication and knowledge representation among heterogeneous Autonomous Undersea Vehicles (AUV's). The process algebra subsumed in this language expresses a generalized optimization framework that contains genetic algorithms, and neural networks as limiting cases.
Expressing Evolutionary Computation, Genetic Programming, Artif icial Life, Autonomous Agents and DNABased Computing in $Calculus  Revised Version
 in $Calculus, Proc. LateBreaking Papers of the Third Annual Genetic Programming Conf. GP98, Univ. of
, 2000
"... Genetic programming, autonomous agents, artif icial life and evolutionary computation share many common ideas. They generally investigate distributed complex processes, perhaps with the ability to interact. It seems to be natural to study their behavior using process algebras, which were designed to ..."
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Cited by 6 (5 self)
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Genetic programming, autonomous agents, artif icial life and evolutionary computation share many common ideas. They generally investigate distributed complex processes, perhaps with the ability to interact. It seems to be natural to study their behavior using process algebras, which were designed to handle distributed interactive systems. $calculus is a higherorder polyadic process algebra for resource bounded computation. It has been designed to handle autonomous agents, evolutionary computing, neural nets, expert systems, machine learning, and distributed interactive AI systems, in general. $calculus has builtin costoptimization mechanism allowing to deal with nondeterminism, incomplete and uncertain information. In this paper, we express in $calculus several subareas of evolutionary computation, including genetic programming, artif icial life, autonomous agents and DNAbased computing. 1
$Calculus of Bounded Rational Agents: Flexible Optimization as Search under Bounded Resources in Interactive Systems
 FUNDAMENTA INFORMATICAE
, 2005
"... This paper presents a novel model for resource bounded computation based on process algebras. ..."
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Cited by 6 (4 self)
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This paper presents a novel model for resource bounded computation based on process algebras.
SAMON: communication, cooperation and learning of mobile autonomous robotic agents
 Proceedings of the 11 th IEEE Intl. Conf. On Tools with Artificial Intelligence
, 1999
"... The Applied Research Laboratory Penn State University “Ocean SAmpling MObile Network” (SAMON) Project is developing the simulation testbed for the oceanographic communities interactions through the Web interface and the simulation based design of Autonomous Ocean Sampling Program missions. In this p ..."
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Cited by 6 (1 self)
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The Applied Research Laboratory Penn State University “Ocean SAmpling MObile Network” (SAMON) Project is developing the simulation testbed for the oceanographic communities interactions through the Web interface and the simulation based design of Autonomous Ocean Sampling Program missions. In this paper, a current implementation of the SAMON is presented, and a formal model based on interactive automata is described. The basic model is extended by process algebra constructs to handle mobility, evolution and learning. To allow cooperation of heterogeneous vehicles a generic behavior messagepassing language is presented.
Concurrency vs. Sequential Interleavings in 1D Threshold Cellular Automata
 APDCM Workshop within Int’l Parallel & Dist. Processing Symp. (IPDPS
, 2004
"... Cellular automata (CA) are an abstract model of finegrain parallelism, as the node update operations are rather simple, and therefore comparable to the basic operations of the computer hardware. In a classical CA, all the nodes execute their operations in parallel, that is, (logically) simultaneous ..."
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Cited by 5 (3 self)
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Cellular automata (CA) are an abstract model of finegrain parallelism, as the node update operations are rather simple, and therefore comparable to the basic operations of the computer hardware. In a classical CA, all the nodes execute their operations in parallel, that is, (logically) simultaneously. We consider herewith the sequential version of CA, or SCA, and compare it with the classical, parallel CA. In particular, we show that there are 1D CA with very simple node state update rules that cannot be simulated by any comparable SCA, irrespective of the node update ordering. While the result is trivial if one considers a single computation on a chosen input, we find it both nontrivial, and having some important and farreaching implications when applied to all possible inputs and, moreover, to the entire nontrivial classes of CA (SCA). We also share some thoughts on how to extend our results herein, and we try motivate the study of genuinely asynchronous cellular automata.
Evolution in Materio: Exploiting the physics of materials for computation
 Int J of Unconventional Computing
, 2008
"... In this position paper we report on our work on programming materials for non conventional computing, using an evolutionary algorithm as the programming technique. The aim is to use the complexity of the physical world to allow sophisticated computation, and in particular as a platform for nonVon N ..."
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Cited by 4 (0 self)
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In this position paper we report on our work on programming materials for non conventional computing, using an evolutionary algorithm as the programming technique. The aim is to use the complexity of the physical world to allow sophisticated computation, and in particular as a platform for nonVon Neumann computation. We have demonstrated this technique using liquid crystal for signal processing and robot control, however we believe that there are many materials that could be programmed in a similar way. It is hoped that such a methodology will provide a general technique for extracting useful computation from matter, possibly at a molecular level. 1
Dichotomy results for fixedpoint existence problems for boolean dynamical systems
, 2007
"... A complete classification of the computational complexity of the fixedpoint existence problem for boolean dynamical systems, i.e., finite discrete dynamical systems over the domain {0, 1}, is presented. For function classes F and graph classes G, an (F, G)system is a boolean dynamical system such ..."
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Cited by 3 (3 self)
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A complete classification of the computational complexity of the fixedpoint existence problem for boolean dynamical systems, i.e., finite discrete dynamical systems over the domain {0, 1}, is presented. For function classes F and graph classes G, an (F, G)system is a boolean dynamical system such that all local transition functions lie in F and the underlying graph lies in G. Let F be a class of boolean functions which is closed under composition and let G be a class of graphs which is closed under taking minors. The following dichotomy theorems are shown: (1) If F contains the selfdual functions and G contains the planar graphs, then the fixedpoint existence problem for (F, G)systems with local transition function given by truthtables is NPcomplete; otherwise, it is decidable in polynomial time. (2) If F contains the selfdual functions and G contains the graphs having vertex covers of size one, then the fixedpoint existence problem for (F, G)systems with local transition function given by formulas or circuits is NPcomplete; otherwise, it is decidable in polynomial time. 1
Constraints on Hypercomputation, in
 Logical Approaches to Computational Barriers: Second Conference on Computability in Europe, CiE 2006
, 2006
"... “To infinity, and beyond!”, Buzz Lightyear, Toy Story, Pixar, 1995. Many attempts to transcend the fundamental limitations to computability implied by the Halting Problem for Turing Machines depend on the use of forms of hypercomputation that draw on notions of infinite or continuous, as opposed to ..."
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Cited by 3 (2 self)
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“To infinity, and beyond!”, Buzz Lightyear, Toy Story, Pixar, 1995. Many attempts to transcend the fundamental limitations to computability implied by the Halting Problem for Turing Machines depend on the use of forms of hypercomputation that draw on notions of infinite or continuous, as opposed to bounded or discrete, computation. Thus, such schemes may include the deployment of actualised rather than potential infinities of physical resources, or of physical representations of real numbers to arbitrary precision. Here, we argue that such bases for hypercomputation are not materially realisable and so cannot constitute new forms of effective calculability. 1
On the Complexity of Image Processing and Pattern Recognition Algorithms
, 1998
"... We study the complexity of image processing and pattern recognition (IPPR) algorithms by their representation as finite cellular automatabased structures. A universal model to represent multilayer homogeneous IPPR algorithms and a technique to compare their quality are required for problems of visio ..."
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Cited by 2 (2 self)
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We study the complexity of image processing and pattern recognition (IPPR) algorithms by their representation as finite cellular automatabased structures. A universal model to represent multilayer homogeneous IPPR algorithms and a technique to compare their quality are required for problems of vision system adaptation, learning, and by the systems for automatic programming. We propose the finite cellular automatabased model for representation of IPPR algorithms and sequential and parallel time complexity measures for this model. Composition and decomposition transformations of proposed structure are suggested and we show that in particular cases they can lead to reduction of complexity. Specific properties of IPPR tasks that are important for their complexity research are discussed.