Cellular networks are significant challenges for high performance data-intensive system designers due to their complexity. Being able to study features and designs before building the actual system is an advantage tha...
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Cellular networks are significant challenges for high performance data-intensive system designers due to their complexity. Being able to study features and designs before building the actual system is an advantage that a simulation model can offer. This paper presents a Petri net models program generator of communication hexagonal grids of arbitrary size for verification of telecommunication systems protocols with a hexagonal cell. Petri nets parametric description is used for automated composition of cellular grid models. The model, basic parameters are: the cellular grid size, the buffer capacity of the communication device, the number of packets in each device buffer. The basic element of the grid consists of internal buffer with the limited size and six ports, which operate in full duplex mode; the destination ports are chosen in nondeterministic way in the model. A program generator of Petri net models is written in the algorithmic language C. The output format type of generated file is represented as a Tina modeling system graphical format. The technique can be used in a wide range of Petri nets applications, including telecommunications, manufacturing systems and programming.
Cellular automata is a nature inspired parallel processing model. It has been proposed several years ago by J. Von Neumann to simulate complex dynamical processes. In the past two decades several models of cellular au...
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ISBN:
(纸本)0769509878
Cellular automata is a nature inspired parallel processing model. It has been proposed several years ago by J. Von Neumann to simulate complex dynamical processes. In the past two decades several models of cellular automata that differ from the original one proposed by Von Neumann have been defined for modeling real-world systems and phenomena. This paper describes the design and implementation of standard and nonstandard parallel cellular automata in the CARPET language. CARPET is a cellular automata based language that has been implemented on MIMD parallel computers. The language is specifically designed for programming cellular computations supporting concise and efficient coding of parallel cellular algorithms. The paper analyzes the main features of the language and describes as they can be exploited to implement different cellular automata on parallel computers, starting from the standard model to its modifications and generalizations. Inhomogeneous, partitioned, asynchronous, and probabilistic cellular automata programmed in CARPET are presented.
Real-life negotiations typically involve multiple parties with (i) different preferences for the different issues and (ii) bargaining strategies which change over time. Such a dynamic environment (with imperfect infor...
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Real-life negotiations typically involve multiple parties with (i) different preferences for the different issues and (ii) bargaining strategies which change over time. Such a dynamic environment (with imperfect information) is addressed in this paper with a multi-population evolutionary algorithm (EA). Each population represents an evolving collection of bargaining strategies in our setup. The bargaining strategies are represented by a special kind of finite automata, which require only two transitions per state. We show that such automata (with a limited complexity) are a suitable choice in a computational setting. We furthermore describe an EA which generates highly-efficient bargaining automata in the course of time. A series of computational experiments shows that co-evolving automata are able to discriminate successfully between different opponents, although they receive no explicit information about the identity or preferences of their opponents. These results are important for the further development of evolving automata for real-life (agent system) applications.
Path planning is a crucial step in automatic programming of coordinate measuring machines(CMMs). The goal is to generate an efficient and collision-free path for the CMM to inspect a collection of points. Previous res...
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Path planning is a crucial step in automatic programming of coordinate measuring machines(CMMs). The goal is to generate an efficient and collision-free path for the CMM to inspect a collection of points. Previous research concentrates on path planning between two points, or sequencing the points without regard to obstacles and collisions. In this paper we propose a practical path planner that considers both sequencing and collision avoidance. The main idea is to create a roadmap of free-space, where the measurement points are nodes in the network. Once all the measurement points are in a single connected component of the roadmap, then a tour of the points is found by solving the appropriate traveling salesperson problem. CMM heuristics are used to construct the roadmap in an efficient and robust manner. The planner has been implemented and tested on real-world mechanical parts.
The authors define a software development environment kernel called MARVEL. Implementing several prototypes and small environments has uncovered some significant flaws and revealed open design problems. Problems conne...
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The authors define a software development environment kernel called MARVEL. Implementing several prototypes and small environments has uncovered some significant flaws and revealed open design problems. Problems connected with the construction and debugging of a process model, with envelope construction, and with support of multiple users are considered. The authors note that they have investigated only a small fraction of the potential for rule-based process modeling and controlled automation. They observe that they do not yet fully understand how rule-based process modeling or controlled automation works and whether the combination is indeed a solid foundation for a software-development environment architecture.< >
This paper presents a novel approach to the programming of automata-based simulation and computation using a machine learning technique. The identification of lattice-based automata for real-world applications is cast...
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This paper presents a novel approach to the programming of automata-based simulation and computation using a machine learning technique. The identification of lattice-based automata for real-world applications is cast as a data mining problem. Our approach to achieving this is to use evolutionary computing and reinforcement learning with performance fed back indicating the predictive accuracy of future behaviour of the given system. The purpose of this work is to develop an approach to identifying automata rules that can achieve good performance using data from a variety of kinds of complex systems
The authors present an algorithm for the generation of mechanical assembly sequences and a proof of its correctness and completeness. The algorithm uses a relational model which describes the geometry of the assembly ...
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ISBN:
(纸本)0818619384
The authors present an algorithm for the generation of mechanical assembly sequences and a proof of its correctness and completeness. The algorithm uses a relational model which describes the geometry of the assembly and the attachments that bind one part to another. The problem of generating the assembly sequences is transformed into the problem of generating disassembly sequences, in which the disassembly tasks are the reverse of feasible assembly tasks. This transformation leads to a decomposition approach in which the problem of disassembling one assembly is decomposed into distinct subproblems, each involving the disassembly of one subassembly. It is assumed that at each assembly task exactly two subassemblies are mated and that all contacts between the parts in the two subassemblies are established. The algorithm yields an AND/OR graph representation of assembly sequences. The correctness of the algorithm is based on the assumption that it is always possible to decide correctly whether two subassemblies can be joined based on geometrical and physical criteria. An approach to compute this decision is given, and bounds for the amount of computation required are presented.< >
A geometric trajectory ensuring the success of an assembly task cannot be determined when the geometric uncertainty is significant. Several solutions like, for instance, passive compliance devices have been applied in...
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A geometric trajectory ensuring the success of an assembly task cannot be determined when the geometric uncertainty is significant. Several solutions like, for instance, passive compliance devices have been applied in order to decrease the influence of geometric uncertainty. However, the general solution appears to be the use of active compliance which implies reaction force/torque feedback, but this use gives rise to some particular problems in the task planning and execution. Sensorial configuration and force information becomes a key point in this field. This paper describes how this sensor information can be used in an assembly fine-motion planner and also during the task execution. The basic concepts have already been implemented and the peg-into-hole assembly task serves as an example to illustrate the results.
A description is given of a technique called middle-out reasoning for the control of search in automatic theorem proving. The authors illustrate it use in the domain of automatic program synthesis. Programs can be syn...
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A description is given of a technique called middle-out reasoning for the control of search in automatic theorem proving. The authors illustrate it use in the domain of automatic program synthesis. Programs can be synthesised from proofs that their logical specifications are satisfiable. Each proof step is also a program construction step. Unfortunately, a naive use of this technique requires a human or computer to produce proof steps which provide the essential structure of the desired program. It is hard to see the justification for these steps at the time that they are made; the reason for them emerges only later in the proof. Such proof steps are often call eureka steps. Middle-out reasoning enables these eureka steps to be produced, automatically, as a side effect of non-eureka steps.< >
The automatic programming of robots to assemble products must cope with assembly planning and task planning problems. These problems are not independent, since an assembly operation may be performed by a different rob...
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The automatic programming of robots to assemble products must cope with assembly planning and task planning problems. These problems are not independent, since an assembly operation may be performed by a different robot task depending on the previous assembly operations performed. Therefore, the cost of assembly operations vary depending on the assembly sequence. This paper deals with the problem of finding the optimum sequence of robot tasks taking into account this variable cost of assembly operations. The proposed approach can cope with products with AND/OR/XOR relations and uses Petri nets as a modelling methodology. The search of a near-optimum sequence of robot tasks is done with an heuristic search of the reachability tree of the Petri net.
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