Reinforcement learning of normative monitoring intensities

Choosing actions within norm-regulated environments involves balancing achieving one’s goals and coping with any penalties for non-compliant behaviour. This choice becomes more complicated in environments where there is uncertainty. In this paper, we address the question of choosing actions in environments where there is uncertainty regarding both the outcomes of agent actions and the intensity of monitoring for norm violations. Our technique assumes no prior knowledge of probabilities over action outcomes or the likelihood of norm violations being detected by employing reinforcement learning to discover both the dynamics of the environment and the effectiveness of the enforcer. Results indicate agents become aware of greater rewards for violations when enforcement is lax, which gradually become less attractive as the enforcement is increased

Obligation Norm Identification in Agent Societies

Most works on norms have investigated how norms are regulated using institutional mechanisms. Very few works have focused on how an agent may infer the norms of a society without the norm being explicitly given to the agent. This paper describes a mechanism for identifying one type of norm, an obligation norm. The Obligation Norm Inference (ONI) algorithm described in this paper makes use of an association rule mining approach to identify obligation norms. Using agent based simulation of a virtual restaurant we demonstrate how an agent can identify the tipping norm. The experiments that we have conducted demonstrate that an agent in the system is able to add, remove and modify norms dynamically. An agent can also flexibly modify the parameters of the system based on whether it is successful in identifying a norm.Norms, Social Norms, Obligations, Norm Identification, Agent-Based Simulation, Simulation of Norms, Artificial Societies, Normative Multi-Agent Systems (NorMAS)

Self Circulation using RFID Technology with KOHA Software at St. Xavier’s College, Kolkata.

St. Xavier’s College Central Library has installed Radio Frequency IDentification (RFID) technology based kiosk for self circulation through open source library management software KOHA. This technology is also improved library annual stock taking, ensure foolproof security and access control i.e. circulation management. This articles briefly describes why our library switch over from barcode based circulation to RFID based circulation, SWOT analysis of RFID technology, self-circulation using RFID technology, types of problem faced during implementation of the new technology and possible remedies. Lastly, the conclusions are drawn based on SWOT analysis

Technical report : issues and strategies of e-learning

An effective e-learning system involves a systematic process of planning, design, development, evaluation, and implementation of a meaningful learning environment where learning is fostered and supported. While there still exists some uncertainty about its role in education and professional training, there is a growing concern about the issues and strategies of e-learning that may be faced by both providers and learners of e-learning in future. This technical report addresses some of the main issues and strategies that are currently encountered in e-learning

Issues in e-learning standards

This paper will discuss the role of e-learning standards for implementing e-learning applications. We briefly define and describe the issues related to e-learning standards to improve performance and availability of elearning content. We also describe the characteristics of standards important for maintaining high quality elearning contents. The various standards are analyzed and the degree of synergy between different standards organizations is identified. We discuss the life cycle for e-learning standards, and the main types of standards to enable the interchange of components in a learning system. The Malaysian experience is presented as a case study

Seasonal variation of arsenic concentrations in tubewells in west Bengal, India.

This study was conducted to monitor the changes in arsenic concentration during different seasons in a one-year period during 2002-2003 in selected tubewells in an arsenic-affected area in the district of South 24 Parganas in West Bengal, India, and to map the location of the wells. Seasonal variations in concentrations of arsenic in water were measured from 74 selected tubewells, ranging in depth from 40 to 500 feet. Water samples were collected from these wells during winter, summer, monsoon, and the following winter in 2002-2003. A global positioning system was used for locating the tubewells, and a geographic information system was used for mapping. There was evidence of seasonal variation in concentrations of arsenic in water (p=0.02) with the minimum average concentration occurring in the summer season (694 microg/L) and the maximum in the monsoon season (906 microg/L). From the winter of 2002 to the winter of 2003, arsenic concentrations increased, irrespective of the depth of the tubewells, from an average of 464 microg/L to 820 microg/L (p<0.001). This extent of variation in arsenic concentration, if confirmed, has important implications for both epidemiological research and mitigation programmes