Catálogo de publicaciones - libros

Knowledge reduction is one of the key problems of rough set theory. In this paper, we investigate some theoretical issues of the reduction of information systems and present a new reduction approach. A closure operator on the power set of attributes is defined. The relations between the closed sets determined by the closure operator and the indiscernibility attribute sets are then investigated. Based on the relations, we can determine a partition on the power of attributes by using the indiscernibility attribute sets. Consequently, the reducts of any subset of attributes in information systems can be derived.

In this paper, a basic architecture of implemented multi-agent ship design system is introduced briefly. And then several cases of conflicts occurred in designing process are described. Finally, conflict resolution method based on case-based reasoning (CBR) approach is presented. Through the help of the developed multi-agent ship design system, a designer can make decisions or resolve some conflicts easily based on the previous resolved similar cases.

This paper describes a method for unfolding a Predicate-net representation of a logistical planning problem, such that it possesses the Markov property. The problem can then be easily converted into a Markov Decision Process (MDP) which can be solved in a tractable manner using standard Dynamic Programming algorithms.

In this paper we present several efficient computational procedures for defeasible reasoning while the plausible and well-defined semantics, viz.preferred models and stable models , are not given up. The proposed algorithms exploit the structural information of defeasible knowledge bases to facilitate efficient computational models.

The optimization of job-shop scheduling is very important because of its theoretical and practical significance. This paper proposes an efficient scheduling method based on artificial immune systems. In the proposed method, the initial population is generated by a proposed scheduling initialization algorithm based on the G&T algorithm, and the models of the vaccination and receptor editing are designed to improve the immune performance. The approach is tested on a set of standard instances taken from the existing standard library. The simulation results validate the effectiveness of the proposed algorithm.

Globalisation of business environments on the Web has given rise to the advent of similar ontologies in which dynamic ontology mapping is called in. Ontology mapping is necessary for ontology interoperability. In this paper, a novel agent-based ontology mapping is presented for agents to operate ontology mapping flexibly in a dynamic environment regardless heterogeneous platforms and different ontology representations. The mapping mechanism is discussed by having a close look at both inherent inter-processes of mapping tasks of an agent and relevant interaction processes. The interrelated processes of agents also enable agent-based ontology mapping to take ontology changes into account whenever needed. A mapping prototype is built for verification.

Dynamic Negative Selection Algorithm Based on Affinity Maturation (DNSA-AM) is proposed to generate dynamic detectors changed with nonselves. But it can not be adapted to the change of self because the match threshold is constant. In this work, a match range model inspired from T-cells maturation is proposed. Based on the model, an augmented algorithm is proposed. There is no match threshold but self-adapted match range. The proposed algorithm is tested by simulation experiment for anomaly detection and compared with DNSA-AM. The results show that the proposed algorithm is more effective than DNSA-AM with several excellent characters such as self-adapted match range and less time complexity.

Simulating a system of agents that navigate in a physical space is a challenging problem when the environment is sophisticated and the number of agents involved is large. We describe experiments in establishing a “virtual Prolog engine” in each agent in a simulation and the scalability and performance issues with such an approach. We report on experiments with a simple predator-prey animat model and discuss how this approach allows us to impart a degree of reasoning and intelligence to what are otherwise very simple animat agents.

This paper investigates the problem of obstacle avoidance and path planning for robotic fish. The swimming of the robot fish to avoid some obstacles is viewed as potential flow around the obstacles. Then the streamlines from the robot position to the target are chosen as the desired paths for the mobile robot to move to the destination. Since there are mature algorithms with high computational efficiency to establish flow field and figure out the streamlines based on fluid mechanics theory, our approach is practical for application. We conduct two example experiments to verify the effectiveness of the approach.

This paper presents a method that enable a domestic robot to show emotions with its facial expressions. The previous methods using built-in facial expressions were able to show only scanty face. To express faces showing complex emotion, mixed emotions and different strengths of emotions, more facial expressions are needed. We have therefore developed a system that converts emotions into “Ifbot” robot’s facial expressions automatically. They are created from emotion parameters , which represent its emotions.