Earticle

게임은 점차 복잡해짐에 따라 게임 환경(맵)도 복잡해지고 있다. 게임 환경(맵)이 복잡해지면 게임 신뢰성을 입증하기 위해서 많은 테스트 프로세스와 방법이 복잡해지는 경향이 있다. 본 논문에서는 자동 생성되는 게임 환경(맵)을 정확하게 진행하는지를 검증하고, 테스트를 줄일 수 있는 테스팅 기법을 AND/OR 그래프와 불식(boolen expression)을 이용하여 제안한다.

As games become ever more complex, game environments (map) are becoming increasingly complex. In this paper, I propose a method to verify the validity of the progression of the automatic map generation as it is being processed. The method It also is proposed to simplify and shorten verification test process using AND/OR graph and Boolean expressions.

The progress of silicon technology enables to implement a highly complex digital system on a given chip area. However, even the modern design environment is not so efficient to catch up with the progress of process technology. Design reuse is a promising approach to designing such a complex system in an efficient way. However, the rigidness and inflexibility of a model has been an obstacle to design reuse. This paper proposes a high-level model management methodology by introducing attributed AND-OR graph(AOG), a (formal semantics for representing the possible structure of a model. Using the formalism enables a designer to extract, extend and reuse the pre-modeled and pre-verified design. A complete process of constructing a cache operational model, extending the model and extracting executable models is exemplified to show effectiveness of the proposed framework.

The objective of this paper is to propose an Extended AND-OR Graph (EAOG)-driven inferential simulation mechanism with which decision makers engaged in electronic commerce (EC) can effectively deal with complicated decision making problem. In the field of traditional expect systems research, AND-OR Graph approach cannot be effectively used in the EC problems in which real-time problem-solving property should be highly required. In this sense, we propose the EAOG inference mechanism for EC problem-solving in which heurisric knowledge necessary for intelligent EC problem-solving can be represented in a form of matrix. The EAOG method possesses the following three characteristics. 1. Realtime inference: The EAOG inference mechanism is suitable for the real-time inference because its computational mechanism is based on matrix computation.2. Matrix operation: All the subjective knowledge is delineated in a matrix form, so that inference process can proceed based on the matrix operation which is computationally efficient.3. Bi-directional inference: Traditional inference method of expert systems is based on either forward chaining or based on either and computational efficiency. However, the proposed EAOG inference mechanism is generically bi-directional without loss of both speed and efficiency.We have proved the validity of our approach with several propositions and an illustrative EC example.

An algorithm that searches the general AND-OR graph is proposed. The convergence and the efficiency of the algorithm is examined and compared with an existing algorithm for the AND-OR graph. It is proved that the proposed algorithm is superior to the existing method both in the quality of the solution and the number of node expansions.

The objective of this paper is to propose a brand new interface mechanism to provide more intelligent decision making support for EC problems. Its main virtue is based on a numerical process mechanism by using an Extended AND-OR Graph (EAOG)-based logic algebra. Using this mechanism, decision makers engaged in electronic commerce (EC) can effectively deal with complicated decision making problems. In the field of traditional expert systems research, AND-OR Graph approach has been suggested as a useful tool for representing the logic flowchart of the forward and/or backward chaining inference methods. However, the AND-OR Graph approach cannot be effectively used in the EC problems in which real-time problem-solving property should be highly required. In this sense, we propose the EAOG inference mechanism for EC problem-solving in which heurisric knowledge necessary for intelligent EC problem-solving can be represented in a form of matrix. Finally, we have proved the validity of our approach with several propositions and an illustrative EC example

The objective of this paper is to apply Extended AND-OR Graph (EAOG)-related techniques to extract knowledge from a specific problem-domain and perform analysis in complicated decision making area. Expert systems use expertise about a specific domain as their primary source of solving problems belonging to that domain. However, such expertise is complicated as well as uncertain, because most knowledge is expressed in causal relationships between concepts or variables. Therefore, if expert systems can be used effectively to provide more intelligent support for decision making in complicated specific problems, it should be equipped with real-time inference mechanism. We develop two kinds of EAOG-driven inference mechanisms(1) EAOG-based forward chaining and (2) EAOG-based backward chaining. and The EAOG method processes the following three characteristics. 1. Real-time inference : The EAOG inference mechanism is suitable for the real-time inference because its computational mechanism is based on matrix computation. 2. Matrix operation : All the subjective knowledge is delineated in a matrix form, so that inference process can proceed based on the matrix operation which is computationally efficient. 3. Bi-directional inference : Traditional inference method of expert systems is based on either forward chaining or backward chaining which is mutually exclusive in terms of logical process and computational efficiency. However, the proposed EAOG inference mechanism is generically bi-directional without loss of both speed and efficiency.