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An expert system is vital in flood warning to determine the decision making output in order for a proper control of the input consisting of river level and rainfall. The river level and rainfall input is naturally stochastic, uncertain and unpredictable. Therefore, a fuzzy logic model of the flood warning expert system has been designed for user to obtain information about flood. This fuzzy model integrates multi-agent and ontology and expected to handle both uncertainty and accuracy issues whereas previous researches focus on handling either uncertainty or accuracy issues only. Simulation of outcome based on river level and rainfall is presented in this study.

In this paper, a flood prediction conceptual model that integrates software agent, ontology and fuzzy logic is proposed. The agent role is to provide information on flood based on river level and rainfall by giving notification to users. The ontology organizes flood knowledge in order to support agent communication. Fuzzy logic will be applied to predict uncertain whether situations.

Problem solving is vital in the computer programming course. It is the earliest topic that is emphasized and more time is allocated to teach the topic. Problem solving requires the problem understanding knowledge that novice students usually lacks. In order to assist novice students in computational problem solving, a multi-agent model is designed.The proposed model is different from existing model in terms of the unique architecture that utilizes agents for information processing, specifically to extract, transform and generate information. Five agents are designed for this purpose namely the GUI, PAC, IPO, Flowchart and Algorithm agents. The model is tested with three different kinds of problem statement and produced correct results.

Comprehending Object-Oriented Programming (OOP) concepts is a difficult task especially for novice students. This usually happens during the transition form learning fundamental concepts to object-oriented (OO) concepts. When given an OO problem to solve, novices find it hard to relate with objects. If novices can view the world based on real objects, this can help them solve their problem of comprehending the OO concepts. In this paper, we propose to design an agent model to understand the semantics of OO Java source codes. The agents are designed based on the Belief-Desire-Intention (BDI) architecture. Three agents namely GUI agent, semantic agent and novice agents are constructed. The GUI agent is controlled by the user to provide source codes examples. The semantic agent submits the source codes to the novice agent and explains the semantic or meaning of the source codes to the novice agent. The process involves source codes comparison technique. This model provides an OOP semantics knowledge representation based on intelligent agents.

To master the mathematics subject, a lot of exercises need to be done. Mathematical problem solving requires writing mathematics equations and symbols to simplify them to get the answer. A step by step guidance is important to make sure that no mistakes occur. This paper presents a study of existing mathematics editor and proposed a web-based model of a mathematics editor using intelligent agent technology based on the Belief, Desires, Intention (BDI) model. The feature to guide the user step by step is incorporated in the proposed model.