Adaptive learning in agents behaviour: A framework for electricity markets simulation

Electricity markets are complex environments, involving a large number of different entities, playing in a dynamic scene to obtain the best advantages and profits. MASCEM (Multi-Agent System for Competitive Electricity Markets) is a multi-agent electricity market simulator that models market players and simulates their operation in the market. Market players are entities with specific characteristics and objectives, making their decisions and interacting with other players. This paper presents a methodology to provide decision support to electricity market negotiating players. This model allows integrating different strategic approaches for electricity market negotiations, and choosing the most appropriate one at each time, for each different negotiation context. This methodology is integrated in ALBidS (Adaptive Learning strategic Bidding System) – a multiagent system that provides decision support to MASCEM's negotiating agents so that they can properly achieve their goals. ALBidS uses artificial intelligence methodologies and data analysis algorithms to provide effective adaptive learning capabilities to such negotiating entities. The main contribution is provided by a methodology that combines several distinct strategies to build actions proposals, so that the best can be chosen at each time, depending on the context and simulation circumstances. The choosing process includes reinforcement learning algorithms, a mechanism for negotiating contexts analysis, a mechanism for the management of the efficiency/effectiveness balance of the system, and a mechanism for competitor players' profiles definition.

Opera-Learning : integración de estándares de distribución de contenidos multimedia y learning objects.

El artículo está incluido en un número monográfico especial con los trabajos del I Simposio Pluridisciplinar sobre Diseño, Evaluación y Descripción de Contenidos Educativos Reutilizables (Guadalajara, Octubre 2004).Resumen basado en el de la publicación

Technology enhanced learning and augmented reality : an application on multimedia interactive books

Multimedia Interactive Book (miBook) reflects the development of a new concept of virtual interpretation of traditional text books and audio-visual content. By encompassing new technological approaches, using augmented reality technology, allows the final user to experience a variety of sensorial stimuli while enjoying and interacting with the content; therefore enhancing the learning process. miBook stands for a global educational intention to enable people not only to access but also to appropriate intellectually valuable contents coming from different linguistic and cultural contexts.

Learning a procedural task: effectiveness of multimedia presentations

Three experiments investigated the effectiveness of presenting procedural information through different media and their combinations. Experiment 1 examined the effectiveness of text, line drawings, text and line drawings, video. and video stills for learning a first aid task. The results showed an advantage of text and line drawings and of the video presentation over the other three conditions for both bandaging performance and answering questions about the task. Experiment 2 showed that the beneficial effect of the combination of text and pictures could not be accounted for simply in terms of a dual coding explanation. Rather, the effectiveness of the media and their combinations was influenced by the extent to which they conveyed action information. Finally, Experiment 3 showed no evidence of a contiguity effect: text and pictures were as effective when presented together on the same screen as when they were presented separately. Copyright © 2000 John Wiley & Sons, Ltd.

e-learning in project management using simulation models: a case study based on the replication of an experiment

Current e-learning systems are increasing their importance in higher education. However, the state of the art of e-learning applications, besides the state of the practice, does not achieve the level of interactivity that current learning theories advocate. In this paper, the possibility of enhancing e-learning systems to achieve deep learning has been studied by replicating an experiment in which students had to learn basic software engineering principles. One group learned these principles using a static approach, while the other group learned the same principles using a system-dynamics-based approach, which provided interactivity and feedback. The results show that, quantitatively, the latter group achieved a better understanding of the principles; furthermore, qualitatively, they enjoyed the learning experience

The plasticity of the mirror system: how reward learning modulates cortical motor simulation of others

Cortical motor simulation supports the understanding of others' actions and intentions. This mechanism is thought to rely on the mirror neuron system (MNS), a brain network that is active both during action execution and observation. Indirect evidence suggests that alpha/beta suppression, an electroencephalographic (EEG) index of MNS activity, is modulated by reward. In this study we aimed to test the plasticity of the MNS by directly investigating the link between alpha/beta suppression and reward. 40 individuals from a general population sample took part in an evaluative conditioning experiment, where different neutral faces were associated with high or low reward values. In the test phase, EEG was recorded while participants viewed videoclips of happy expressions made by the conditioned faces. Alpha/beta suppression (identified using event-related desynchronisation of specific independent components) in response to rewarding faces was found to be greater than for non-rewarding faces. This result provides a mechanistic insight into the plasticity of the MNS and, more generally, into the role of reward in modulating physiological responses linked to empathy.

A touch of sugar : a multimedia case study to facilitate student dietitians learning about the clinical management of diabetes

This paper describes the development, implementation and evaluation of a multimedia case study on dietetic case management of diabetes. A multimedia web-based program was developed to use the interactive capacity of the web-based environment to enable student dietitians to develop the skills of clinical reasoning and to trigger their learning about the nutritional management of diabetes. A case study of a person with diabetes was developed using a simulated medical history, video clips and sound clips. The students were asked to manage the patient online by responding to the patient's questions, attending a team meeting and outpatient clinic, attending to food service tasks and responding to visual cues. Tutors were able to access the student's responses to submissions online. Evaluation of the program was by questionnaire, which gathered quantitative and qualitative data on the student's perceptions of their experiences in using the web-based case. The students rated the content and the interactive parts of the case highly but experienced technical difficulties and found the case took too much time to complete.

Studio - learning and teaching environment for multimedia

This paper is a case study of the introduction of a studio environment for the teaching of multimedia practice. This change is in the context of multimedia being placed within an information technology degree program, where the conventions and traditions of computer science prevail. The studio based teaching was accepted and now new studios are being built at the university and a research project is proposed with the Queensland University of Technology to explore further teaching and learning issues using studio
teaching methods.

New learning networks and their invisible students : policy as simulation or the avoidance game?

Within a climate of policy hysteria, it is often claimed that a 'preoccupation with performance' develops, focussing on individual success stories, resulting in 'fad-like waves of adoption and abandonment'. Within this increasing pace and intensity of reform, new networks are formed and new relationships developed, with key players taking on new forms of identity to morph into the constantly changing policy climate. Despite continued evidence of young people's pathways from school being more like mosaic than linear, new policy still seeks to define and limit the possible lines of flight and trajectories, closely managing the education and training of young people at risk. In Victoria, the major policy initiative has involved the establishment of LLENs, the local all purpose solution to young people who might not be sticking to the linear policy pathway. So are we involved in 'an avoidance game', filling up the post compulsory policy space with more and more policies, which in fact seek to continue to regulate and constrain young people, rather than supporting them? This paper interrogates the policies and practices which have created the learning networks, of the SGR LLEN through policy analysis and case studies.

Optimising discrete event simulation models using a reinforcement learning agent

A reinforcement learning agent has been developed to determine optimal operating policies in a multi-part serial line. The agent interacts with a discrete event simulation model of a stochastic production facility. This study identifies issues important to the simulation developer who wishes to optimise a complex simulation or develop a robust operating policy. Critical parameters pertinent to 'tuning' an agent quickly and enabling it to rapidly learn the system were investigated.

Extending robust industrial optimisation using simulation and reinforcement learning

Traditional optimisation methods are incapable of capturing the complexity of today's dynamic manufacturing systems. A new methodology, integrating simulation models and intelligent learning agents, was successfully applied to identify solutions to a fundamental scheduling problem. The robustness of this approach was then demonstrated through a series of real-world industrial applications.

Investigation into the design and development of the Toad Interactive Multimedia Program (TIMMP) and its use by first year biology undergraduates learning dissection procedures and in situ functional anatomy

Investigates how first year biology undergraduates learn dissection when they have access to such interactive multimedia technology. Related design and developmental factors were evaluated in relation to how they helped students learn the content in the multimedia program. Through the use of interactive technology students can learn at their own pace without the need for actual animal dissection.

Simulation-based learning for control of complex conveyor networks

This research investigated the problem of path planning in complex conveyor networks. A reinforcement learning approach was applied to derive a control strategy for routing traffic. The derived strategy was verified in real world systems and was found to improve network performance by prioritising traffic flows and balancing network load.