Results 11  20
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39
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
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.
Computational Complexity of Some Enumeration Problems About Uniformly Sparse Boolean Network Automata
 ELECTRONIC COLLOQUIUM ON COMPUTATIONAL COMPLEXITY, REPORT NO. 159 (2006)
, 2006
"... We study the computational complexity of counting the fixed point configurations (FPs), the predecessor configurations and the ancestor configurations in certain classes of graph or network automata viewed as discrete dynamical systems. Some early results of this investigation are presented in two r ..."
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We study the computational complexity of counting the fixed point configurations (FPs), the predecessor configurations and the ancestor configurations in certain classes of graph or network automata viewed as discrete dynamical systems. Some early results of this investigation are presented in two recent ECCC reports [39, 40]. In particular, it is proven in [40] that both exact and approximate counting of FPs in the two closely related classes of Boolean network automata, called Sequential and Synchronous Dynamical Systems (SDSs and SyDSs, respectively), are computationally intractable problems when each node is required to update according to a monotone Boolean function. In the present paper, we further strengthen those results by showing that the intractability of exact enumeration of FPs of a monotone Boolean SDS or SyDS still holds even when (i) the monotone update rules are restricted to linear threshold functions, and (ii) the underlying graph is uniformly sparse. By uniform sparseness we mean that every node in the graph has its degree bounded by for a small value of constant. In particular, we prove that exactly enumerating FPs in such SDSs and SyDSs remains #Pcomplete even when no node degree exceeds. Among other consequences, we show that this result also implies intractability of determining the exact memory capacity of discrete Hopfield networks with uniformly sparse and nonnegative integer weight matrices.
Hierarchy of DiscreteTime Dynamical Systems
, 1994
"... This paper is an attempt to unify classical automata theory and dynamical systems theory. We present a notion of generalized dynamical systems, allowing us to compare properties of both types of systems. Then we etablish a hierachy of dynamical systems, including Turing machines, cellular automata a ..."
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This paper is an attempt to unify classical automata theory and dynamical systems theory. We present a notion of generalized dynamical systems, allowing us to compare properties of both types of systems. Then we etablish a hierachy of dynamical systems, including Turing machines, cellular automata and classical dynamical systems. We finish with some conclusions and motivations for future work. 1 Introduction The theory of finite automata has always been an important field of computer science. Automata, languages, grammars, have been extensively studied [1, 2]. Automata recognize languages and grammars produce languages. Among others, the most studied are finite automata, pushdown automata, Turing machines. The Chomsky hierarchy for languages and grammars is also very well established: regular, contextfree, contextsensitive, general grammars generate languages with the same names. The theory of dynamical systems, chaos, attractors [3, 4], is an important field of mathematics and phys...