Fuzzy logic controllers have been proven to be an effective means of solving real world control issues. One of the difficulties in the construction of fuzzy controllers is the design of the rule base under which they ...
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Fuzzy logic controllers have been proven to be an effective means of solving real world control issues. One of the difficulties in the construction of fuzzy controllers is the design of the rule base under which they operate. This paper investigates the application of evolutionary programming as an iterative learning process for the fuzzy rule base. This approach is applied to the problem of an elevator control system. The system is optimized for efficiency and smoothness by encouraging higher velocities with minimal changes in acceleration, and by discouraging violations of the design parameters for the system. The performance of the evolved system compares favorably to that of fuzzy controllers designed using traditional methods.
Cost-based abduction (CBA) is an important AI formalism for representing knowledge under uncertainty. In this formalism, evidence to be explained is treated as a goal to be proven, proofs have costs based on how much ...
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Cost-based abduction (CBA) is an important AI formalism for representing knowledge under uncertainty. In this formalism, evidence to be explained is treated as a goal to be proven, proofs have costs based on how much needs to be assumed to complete the proof, and the set of assumptions needed to complete the least-cost proof are taken as the best explanation for the given evidence. The problem of finding the least-cost proof for a given CBA system is NP-hard and current techniques have exponential complexity in the worst case. Computational intelligence approaches to this problem have not been previously explored. In this paper, we show how high order recurrent networks can be used to find least-cost proofs for CBA instances. We describe experimental results on 80 CBA instances using networks of up to 68 neurons.
Implementation of a fuzzy logic controller on an FPGA using VHDL is presented in this paper. The basic components of the fuzzy logic controller are designed using VHDL and a Xilinx virtex FPGA is used for implementati...
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Implementation of a fuzzy logic controller on an FPGA using VHDL is presented in this paper. The basic components of the fuzzy logic controller are designed using VHDL and a Xilinx virtex FPGA is used for implementation. The fuzzy logic controller with an 8-bit input, 8-bit output is tested by controlling single disk of an ECP torsional plant.
Short product cycles and rapidly changing requirements are increasingly forcing developers to use agile development strategies like extreme programming and test-driven development. At the same time, hierarchical softw...
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Short product cycles and rapidly changing requirements are increasingly forcing developers to use agile development strategies like extreme programming and test-driven development. At the same time, hierarchical software design strategies such as component based software engineering are becoming necessary to overcome increasing software complexity. In this paper, we present a test-driven component development framework that encapsulates test code in a mirror component for automated testing during development, and as an executable semantic to simplify assessment and to increase trustworthiness of software systems.
We show that automata theory can be useful for engineering, developing and documenting multiagent systems. Algorithmization and programming principles for logic control are formulated, regarding algorithms and program...
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We show that automata theory can be useful for engineering, developing and documenting multiagent systems. Algorithmization and programming principles for logic control are formulated, regarding algorithms and programs as finite automata.
This paper defines PT'-resolution which is the integration of PT-resolution and approximate reasoning. PT-resolution is a deduction method based on partial intersection and truncation. The integration enables the ...
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This paper defines PT'-resolution which is the integration of PT-resolution and approximate reasoning. PT-resolution is a deduction method based on partial intersection and truncation. The integration enables the deduction to handle quantitative data in an approximate manner. It is proved that the PT'-resolution is consistent with PT-resolution.
This paper summarizes an experiment in the formal specification of the visual language for the geometric machine model, denoted by GMVL. The specification follows the approach proposed in the GENGED project, of the T....
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This paper summarizes an experiment in the formal specification of the visual language for the geometric machine model, denoted by GMVL. The specification follows the approach proposed in the GENGED project, of the T. U. Berlin by R. Bardohl and C. Ermel (2001). In the GMLV, supported by a visual alphabet and a visual grammar, a process constructor is represented by a graph transformation related to a rule application in the visual grammar. The syntactical level includes an abstract syntax, related to the logical level of the graphic structures, and a concrete syntax, concerned with the graphical layout. Some of the important benefits from a visual approach, that overhaul and stimulate the programming the GM model, are emphasized in the spacial representation of functional composition and recursive definitions of parallel and non-deterministic processes.
This paper brings an idea of a multi-agent system, in which agents use logical programming for reasoning and interaction. To cope with changing environment agents use default rules and default reasoning, which enables...
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This paper brings an idea of a multi-agent system, in which agents use logical programming for reasoning and interaction. To cope with changing environment agents use default rules and default reasoning, which enables them to reason using default and concise knowledge received from other agents (i.e. rules and exceptions). Moreover predicates in the systems are classified according to the degree of trust and while reasoning this classification is taken into account. Concepts based on default theory stratification have also been used.
Inductive logic programming is an attractive and expressive paradigm for machine learning. A drawback of inductive logic programs is their demanding computational requirements. We present of FPGA-based multi-processor...
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Inductive logic programming is an attractive and expressive paradigm for machine learning. A drawback of inductive logic programs is their demanding computational requirements. We present of FPGA-based multi-processor architecture aimed at fast execution of such programs. The architecture exploits both coarse-grained parallelism at the query level, and fine-grained parallelism in the unification algorithm. Instructions are not required, and the components are customised for a hypothesis space referring only to ground unit clauses in the background knowledge. It also benefits from a distributed memory hierarchy, with a method for including background knowledge to eliminate instructions. The effectiveness of this architecture is demonstrated using a large organic chemistry data set. The proposed architecture is faster and smaller than our previous design based on multiple instruction processors. A single customised processor at 38 MHz can run 9 times faster than a Pentium 4 processor at 1.8GHz; a Xilinx XCV2000E device can accommodate 24 processors running in parallel.
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