On Agent Communication in Large Groups

The problem is fundamental and natural, yet deep - to simulate the simplest possible form of communication that can occur within a large multi-agent system. It would be prohibitive to try and survey all of the research on communication in general so we must restrict our focus. We will devote our efforts to synthetic communication occurring within large groups. In particular, we would like to discover a model for communication that will serve as an abstract model, a prototype, for simulating communication within large groups of biological organisms

Contribution of internet to a democratic society

Equitable information access and freedom of expression are viewed as essential aspects of a truly democratic society, whereby all citizens are kept informed and enlightened. A natural extension of this ideal is the human need and desire to communicate and exchange information with others. With the advent of the internet, and extraordinary growth in information and communication technologies in recent years, more information than ever before is made freely available and easily shared. Information is now available in a plethora of digital formats and can be exchanged across time zones, countries and groups in seconds, and this makes communicating and connecting easier and more efficient. This paper discusses the role of free flow of information through internet in shaping democratic values. This paper discusses the role of internet as a democratic tool that allows significant benefits for society at large in a dynamic global environment. It concludes that internet’s contribution to democracy has not fully matured and its potential to revitalize democracy and outweigh potential for oppression and control is a dynamic and multifaceted issue in the global environment. Internet, however, has a passive rather than active role in a democratic society. It, thus, influences only those who interact with it

Bayesian expert systems and multi-agent modeling for learner-centric Web-based education

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, 2005.Includes bibliographical references (leaves 140-150).Online distance education provides students with a wealth of information. When students submit course-related search term queries, the search engine returns the search hits based on keyword and topic match. A student's particular learning style is not taken into consideration. For instance, a visually oriented student may benefit more than others from viewing videos and interacting with simulations. We address this problem by designing and developing a knowledge-based system for the initial assessment of students' learning styles. Each student's membership in a learning style dimension (e.g. visual or verbal) is estimated probabilistically. We reach this probability value by using a sequential Bayesian approach to administer a dynamic questionnaire that aims to attain a desired confidence level estimate with the minimal number of questions. A multi-agent online tutoring system uses this initial learning style model to start suggesting learning material matching the student's style. Each agent is an expert in a learning style dimension and can suggest the learning materials matching the student's style. In addition, these agents closely follow the student's evolving preferences and continuously update the stochastic model based on the student's online activities. When the student searches for course material, the multi-agent system delivers the search matches in a cycle-free preference order influenced by the students' multi-dimensional learning style model.by Ralph Rizkallah Rabbat.Ph.D

Chaordic learning systems: reconceptualising pedagogy for the digital age

This article focuses on an explorative and experimental project seeking to implement Chaordic Learning Systems (CLS) as a pedagogic approach in Higher Education. We outline a project that embraced technologies of Web 2.0 to show how both physical and virtual spaces can be used to support and develop a strong and dynamic learning community in which staff and students work alongside each other to co-produce learning resources. Drawing on theories of Communities of Practice and Situated Learning a new teaching framework was introduced to a Level 5 undergraduate module (7.5 ECTS credits) that had not, until this project, used both face-to-face and online learning tools to engage students in the critical and discursive debates pertaining to sport and physical culture. We undertook this project with the belief that Higher Education should be concerned with answering the calls of an increasingly digital society for whom learning is not restricted by the physical boundaries of the university or the political landscape within which learning finds itself

Understanding Video Adoption: An Insider Action Researcher’s Case Study Using the Concerns-Based Adoption Model to Facilitate a Community of Inquiry in Online Courses

This research explored how an insider change agent constructs a holistic understanding of a user’s adoption of video to facilitate the change adoption process and establish a community of inquiry in online courses. The case study was guided by tenets of change theory and constructivism emphasizing the personal and collaborative experience of the change adoption process. The Concerns-Based Adoption Model (CBAM) constructs of Stages of Concern (SoC), Levels of Use (LoU) and Innovation Configuration (IC), along with the Community of Inquiry (CoI) model elements of presence aligned with the theoretical frameworks and guided data collection and analysis. Using five iterative action research cycles of plan, act, observe, and reflect, qualitative data descriptions were drawn from quantitative surveys, focused interviews, direct observations, and participant and researcher reflections. Participant profiles were constructed using concerns profiles, levels of use rating, and implementation fidelity. The analysis of data findings were based on collaborative discussions between the researcher and participants and resulted in the development of individualized action plans and targeted interventions for each participant and the researcher

Agents for educational games and simulations

This book consists mainly of revised papers that were presented at the Agents for Educational Games and Simulation (AEGS) workshop held on May 2, 2011, as part of the Autonomous Agents and MultiAgent Systems (AAMAS) conference in Taipei, Taiwan. The 12 full papers presented were carefully reviewed and selected from various submissions. The papers are organized topical sections on middleware applications, dialogues and learning, adaption and convergence, and agent applications

Proceedings, MSVSCC 2017

Proceedings of the 11th Annual Modeling, Simulation & Visualization Student Capstone Conference held on April 20, 2017 at VMASC in Suffolk, Virginia. 211 pp

Remote Access to a Prototyping Laboratory

There is a growing global demand for continuing adult higher education particularly in science and engineering subjects. New technologies are emerging which would enable the development of a Remote Access Laboratory for rapid prototyping of Artificial Intelligence, as a learning environment for mechatronic engineering, in which high precision electromechanical devices are designed to exhibit autonomous behaviour. Secondary research investigated the learning theories for a Remote Access Laboratory, and the current practices for distance learning, involving groupware in shared activity 'collaboratories'. Having determined that the laboratory would need a multi-user interactive environment architecture, with the requirement for adaptability to rapid developments,a distributed software architecture was selected. The laboratory design was subsequently argued to be best served by Intelligent Agents in a Multi-Agent system. The aims of the research were to establish the viability of a Remote Access Laboratory for mechatronic experimentation, and to evaluate the technologies required to implement such a laboratory environment for rapid prototyping. These were achieved by developing a novel user interface, based on a multi-functional screen layout, and a graphical specification facility to provide robotic navigation that is intuitive to use and does not require text-based programming. The research investigated the prototyping of robotic behaviour, which used Programming by Demonstration as an innovative technique to prototype robot navigation. The method of designing behaviours met an anticipated need to allow the robot to interact with an environment, to achieve goals under conditions of uncertainty, while requiring a level of abstraction in the behaviour design. The interface structured a composite of the designed behaviours into prototype Artificial Intelligence using a hierarchical behaviour architecture, which complied with the principles of Object Orientated programming. This was subsequently a new and original programming method to facilitate rapid prototyping of Artificial Intelligence design and structuring. Experimentation involved 20 participants attempting to accomplish a series of tasks which involved using the prototyped interface and an existing text-based robot programming system. The participants were profiled by their formal qualifications, knowledge and experience. The experimental data obtained were used to establish a comparative measure of the prototype interface success compared with an existing distance-learning, home experiment kit, in the form of a small controllable model vehicle. The data obtained provided strong evidence to support the hypothesis that a Programming by Demonstration based system for rapid prototyping is more flexible and easier to use than a previously existing distance learning text-based system. The Programming by Demonstration system showed great promise, being quicker for prototyping, and more intuitive. The learning interface design pioneered new techniques and technologies for rapid prototyping of Artificial Intelligence in a Mechatronics Remote Access Laboratory

An Evolutionary Upgrade of Cognitive Load Theory: Using the Human Motor System and Collaboration to Support the Learning of Complex Cognitive Tasks

Cognitive load theory is intended to provide instructional strategies derived from experimental, cognitive load effects. Each effect is based on our knowledge of human cognitive architecture, primarily the limited capacity and duration of a human working memory. These limitations are ameliorated by changes in long-term memory associated with learning. Initially, cognitive load theory's view of human cognitive architecture was assumed to apply to all categories of information. Based on Geary's (Educational Psychologist 43, 179-195 2008; 2011) evolutionary account of educational psychology, this interpretation of human cognitive architecture requires amendment. Working memory limitations may be critical only when acquiring novel information based on culturally important knowledge that we have not specifically evolved to acquire. Cultural knowledge is known as biologically secondary information. Working memory limitations may have reduced significance when acquiring novel

Modeling of Multi-Agent Systems in the Presence of Uncertainty: The Case of Information Economy

We discuss some issues involved in modeling of complex systems composed of dynamically interacting agents. We describe a prototype of simulation environment INFOGEN created for modeling of such systems with the aim of evaluating strategies of enterprises in the information economy, but applicable to general multiagent systems. The case study is presented along with the mathematical description of the multi-agent systems