Agent-Based Hybrid Intelligent Systems: An Agent-Based Framework for Complex Problem Solving

Pt. I. Fundamentals of hybrid intelligent systems and agents -- 1. Introduction -- 2. Basics of hybrid intelligent systems -- 3. Basics of agents and multi-agent systems -- Pt. II. Methodology and framework -- 4. Agent-oriented methodologies -- 5. Agent-based framework for hybrid intelligent systems --6. Matchmaking in middle agents -- Pt. III. Application systems -- 7. Agent-based hybrid intelligent system for financial investment
planning -- 8. Agent-based hybrid intelligent system for data mining -- Pt. IV. Concluding remarks -- 9. The less the more -- App. Sample source codes of the agent-based financial planning system

Limits to problem solving in science

Popper, Polanyi and Duncker represent the widely held position that theoretical and experimental scientific research are motivated by problems to which discoveries are solutions. According to the argument here, their views are unsupported and - in light of counter-instances, anomalous chance discoveries, and the force of curiosity - over-generalized.

Understanding problem solving in requirements engineering : debating creativity with IS practitioners

RE is well-recognised as a creative problem solving activity by the systems development community. However, while substantial research has been conducted and knowledge gained about creativity in the general psychology of problem solving, creativity as it applies to RE remains a relatively unexplored area - one that has neither been comprehensively studied, nor highly recognised, as a research topic of importance. This paper attempts to address the above mentioned gap by presenting findings from a recent focus group study of creativity in RE as perceived by a group of RE practitioners. We provide a conceptual framework for understanding creativity in RE, which may be of use to requirements engineers attempting to enable more creative approaches and results, as well as adding to the existing, limited body of research in this area.

Spatial thinking processes employed by primary school students engaged in mathematical problem solving

This thesis describes changes in the spatial thinking of Year 2 and Year 4 students who participated in a six-week long spatio-mathematical program. The main investigation, which contained quantitative and qualitative components, was designed to answer questions which were identified in a comprehensive review of pertinent literatures dealing with (a) young children's development of spatial concepts and skills, (b) how students solve problems and learn in different types of classrooms, and (c) the special roles of visual imagery, equipment, and classroom discourse in spatial problem solving. The quantitative investigation into the effects of a two-dimensional spatial program used a matched-group experimental design. Parallel forms of a specially developed spatio-mathematical group test were administered on three occasions—before, immediately after, and six to eight weeks after the spatial program. The test contained items requiring spatial thinking about two-dimensional space and other items requiring transfer to thinking about three-dimensional space. The results of the experimental group were compared with those of a ‘control’ group who were involved in number problem-solving activities. The investigation took into account gender and year at school. In addition, the effects of different classroom organisations on spatial thinking were investigated~one group worked mainly individually and the other group in small cooperative groups. The study found that improvements in scores on the delayed posttest of two-dimensional spatial thinking by students who were engaged in the spatial learning experiences were statistically significantly greater than those of the control group when pretest scores were used as covariates. Gender was the only variable to show an effect on the three-dimensional delayed posttest. The study also attempted to explain how improvements in, spatial thinking occurred. The qualitative component of the study involved students in different contexts. Students were video-taped as they worked, and much observational and interview data were obtained and analysed to develop categories which were described and inter-related in a model of children's responsiveness to spatial problem-solving experiences. The model and the details of children's thinking were related to literatures on visual imagery, selective attention, representation, and concept construction.

Meanings of the terms, problem and problem solving across the school curriculum

Many teachers at all levels of education find it hard to articulate what the terms problem and problem solving mean. This study was designed to explore the meanings of these concepts held by people involved in education.

Tasks and pedagogies that facilitate mathematical problem solving

This is a report from one aspect of a project seeking to identify teacher actions that support mathematical problem solving. The project developed a planning and teaching model that describes the type of classroom tasks that can facilitate mathematical problem solving, the sequencing of the tasks, the nature of teaching heterogeneous groups, ways of dfferentiating tasks, and particular pedagogies. We report here one teacher's implementation of the
model using a unit of work that he planned and taught. The report provides important insights into the implementation of the theoretically founded model and the responses of students. We found that the model can be used for planning and teaching and for encouraging problem solving. The model has a positive effect on the learning of most students. Specific teachers actions were identified in order to address the needs of the students we are most
keen to support, those experiencing dfficulties.

Beyond Simon’s means-ends analysis : natural creativity and the unanswered ‘why’ in the design of intelligent systems for problem-solving

Goal-directed problem solving as originally advocated by Herbert Simon’s means-ends analysis model has primarily shaped the course of design research on artificially intelligent systems for problem-solving. We contend that there is a definite disregard of a key phase within the overall design process that in fact logically precedes the actual problem solving phase. While systems designers have traditionally been obsessed with goal-directed problem solving, the basic determinants of the ultimate desired goal state still remain to be fully understood or categorically defined. We propose a rational framework built on a set of logically interconnected conjectures to specifically recognize this neglected phase in the overall design process of intelligent systems for practical problem-solving applications.