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**1 - 5**of**5**### A View of Costed Pi-calculus for Particle Swarm Optimization with QoS-aware Service Selection ★

"... This paper presents a novel computation model for Particle Swarm Optimization (PSO) based on process algebras, which consists of some additional primitives, such as beam channel, logic parallels, logic choices, cost, cost choices and so forth. In this calculus, everything is a cost expression includ ..."

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This paper presents a novel computation model for Particle Swarm Optimization (PSO) based on process algebras, which consists of some additional primitives, such as beam channel, logic parallels, logic choices, cost, cost choices and so forth. In this calculus, everything is a cost expression including the cost of a expression, the choice of expressions, or even the search procedure of PSO itself. As an instance of the applications using discrete PSO, QoS-aware web service selection can be modeled naturally in this calculus and the algebraic and physical representation of the solution is imported to guideline the design of discrete scheme of PSO. In the experiments in simulation platform, the results show that the proposed approach can effectively formalize the QoS-aware web service composition in both algebraic and physical perspectives, and also generate the well-scrutinized service in accordance with the high QoS cost requirements in the acceptable time.

### The kΩ-Optimization Distributed Meta-Level Control for Cooperation and Competition of Bounded Rational Agents

"... Abstract. The $-calculus process algebra for problem solving applies the cost performance measures to converge to optimal solutions with minimal problem solving costs. The same meta-level kΩ-optimization control can be used to find the best quality solutions (expressed as optimization problems), the ..."

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Abstract. The $-calculus process algebra for problem solving applies the cost performance measures to converge to optimal solutions with minimal problem solving costs. The same meta-level kΩ-optimization control can be used to find the best quality solutions (expressed as optimization problems), the most effective solutions (expressed as search optimization problems), or to find solutions representing the tradeoff between the best quality and least costly solutions (expressed as totally optimization problems). The total optimization is described as an instance of multiobjective optimization. In this paper we demonstrate that cooperation and competition of multiagent systems can be naturally investigated as a multiobjective optimization too.

### The $-Calculus Process Algebra of Bounded Rational Agents Applied to Selected Problems in Bioinformatics

"... The solutions of bioinformatics problems very often require searching through very large search spaces. A new technique for the solutions of hard computational problems in bioinformatics is investigated. This is the $calculus process algebra for problem solving that applies the cost performance meas ..."

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The solutions of bioinformatics problems very often require searching through very large search spaces. A new technique for the solutions of hard computational problems in bioinformatics is investigated. This is the $calculus process algebra for problem solving that applies the cost performance measures to converge to optimal solutions with minimal problem solving costs. We demonstrate that the $-calculus generic search method, called the kΩ-optimization, can be used to solve the sequence alignment problem. 1

### Computational Completeness of Interaction Machines and Turing Machines

"... In the paper we prove in a new and simple way that Interaction machines are more powerful than Turing machines. To do that we extend the definition of Interaction machines to multiple interactive components, where each component may perform simple computation. The emerging expressiveness is due to t ..."

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In the paper we prove in a new and simple way that Interaction machines are more powerful than Turing machines. To do that we extend the definition of Interaction machines to multiple interactive components, where each component may perform simple computation. The emerging expressiveness is due to the power of interaction and allows to accept languages not accepted by Turing machines. The main result that Interaction machines can accept arbitrary languages over a given alphabet sheds a new light to the power of interaction. Despite of that we do not claim that Interaction machines are complete. We claim that a complete theory of computer science cannot exist and especially, Turing machines or Interaction machines cannot be a complete model of computation. However complete models of computation may and should be approximated indefinitely and our contribution presents one of such attempts.