Catálogo de publicaciones - libros

We present a feature selection method by fuzzy inference and its application to spam-mail filtering in this work. The proposed fuzzy inference method outperforms information gain and chi squared test methods as a feature selection method in terms of error rate. In the case of junk mails, since the mail body has little text information, it provides insufficient hints to distinguish spam mails from legitimate ones. To address this problem, we follow hyperlinks contained in the email body, fetch contents of a remote web page, and extract hints from both original email body and fetched web pages. A two-phase approach is applied to filter spam mails in which definite hint is used first, and then less definite textual information is used. In our experiment, the proposed two-phase method achieved an improvement of recall by 32.4% on the average over the 1 phase or the 2 phase only works.

This paper first proposes a novel transitive dependence theory. Based on the proposed transitive dependence theory, a dynamic virtual organization formation framework has been worked out which includes service discovery, transitive dependence based reasoning for organization partners search and organization resolution.

Some actual multi-agent automated negotiation systems using auction mechanism in e-commerce are inefficient, as buyer negotiation agents are lack of enough rationality and uneasy to determine appropriate bid price automatically according to different circumstance. In order to improve the auction-based negotiation efficiency of multi-agent system in e-commerce, this paper proposes a model of game agent for auction-based negotiation and a bid negotiation algorithm based on game theory, which provide a new effective way to establish buyer game agent for making buyer agent determine price more accurately and bid more rationally. As buyer agents bid in a more rational way, auction agents and buyer agents can finish negotiation more efficiently.

In this paper, we design a novel autonomous mobile robot which uses quantum sensors to detect faint signals and fulfills some learning tasks using quantum reinforcement learning (QRL) algorithms. In this robot, a multi-sensor system is designed with SQUID sensor and quantum Hall sensor, where quantum sensors coexist with traditional sensors. A novel QRL algorithm is applied and a simple simulation example demonstrates its validity.

This paper focuses on the problem of cooperative search using a team of Unmanned Aerial vehicles (UAVs). The objective is to visit as many unknown area as possible, while avoiding collision. We present an approach which combines model predictive control(MPC) theory with genetic algorithm(GA) to solve this problem. First, the team of UAVs is modelled as a controlled system, and its next state is predicated by MPC theory. According to the predicted state, we then establish an optimization problem. By use of GA, we get the solution of the optimization problem and take it as the input of the controlled system. Simulation results demonstrate the feasibility of our algorithm.

This paper demonstrates the self-organization evolution of distributed Supply Networks (SNs) based on fitness landscape theory. The environment and the internal mechanism are the origin of SN evolution. The SN emerges from the local interaction of the firms to fulfill the stochastic demands. The collaboration among firms is path dependence. The evolution of a SN is self-reinforcement and sensitive to initial conditions, which may lead to multiple equilibrium state and chaos. The evolution result is non-deterministic and can not be predicted precisely. The long-term strategy is better than short-term strategy for a firm in SN collaboration to adapt to the environment.

Dynamic architecture of multi-agent systems (MAS) is very important for the critical systems. As the existing formal specifications cannot describe the dynamic architecture of MAS, while -calculus is specially suited for the description and analysis of concurrent systems with dynamic or evolving topology, a formal approach using -calculus is presented to describe MAS. -calculus can describe the interactions among agents and permit their analysis for some key properties, e.g. deadlock, bisimilarity. By constructing a MAS model in electronic commerce, the modeling process using -calculus are illustrated.

Cooperation between storage devices is an important aspect of autonomic storage system. By employing multiple distributed storage resources, storage system can greatly improve its performance. In this paper, agent-based methodology is introduced to build an autonomic storage system infrastructure. To select appropriate storage devices, queuing models are established to estimate the future storage device performance. A replica selection method and a data allocation algorithm are presented to gain an aggregate transfer rate according to the predicted performance. The results show that our models are useful for evaluating the mean response time of storage devices.

A new distributed spam filter system based on mobile agent is proposed in this paper. We introduce the application of mobile agent technology to the spam filter system. The system architecture, the work process, the pivotal technology of the distributed spam filter system based on mobile agent, and the Naive Bayesian filter method are described in detail. The experiment results indicate that the system can prevent spam emails effectively.

This paper presents the hexagon-based Q-leaning to find a hidden target object with multiple robots. We set up an experimental environment with three small mobile robots, obstacles, and a target object. The robots were out to search for a target object while navigating in a hallway where some obstacles were placed. In this experiment, we used two control algorithms: an area-based action making (ABAM) process to determine the next action of the robots and hexagon-based Q-learning to enhance the area-based action making process.