A Feature Analysis Framework for Evaluating Multi-Agent System Development Methodologies

This paper proposes a comprehensive and multi-dimensional feature analysis framework for evaluating and comparing methodologies for developing multi-agent systems (MAS). Developed from a synthesis of various existing evaluation frameworks, the novelty of our framework lies in the high degree of its completeness and the relevance of its evaluation criteria. The paper also presents a pioneering effort in identifying the standard steps and concepts to be supported by a MAS-development process and models

Integrating BDI agents with Agent-based simulation platforms

Agent-Based Models (ABMs) is increasingly being used for exploring and supporting decision making about social science scenarios involving modelling of human agents. However existing agent-based simulation platforms (e.g., SWARM, Repast) provide limited support for the simulation of more complex cognitive agents required by such scenarios. We present a framework that allows Belief-Desire Intention (BDI) cognitive agents to be embedded in an ABM system. Architecturally, this means that the "brains" of an agent can be modelled in the BDI system in the usual way, while the "body" exists in the ABM system. The architecture is exible in that the ABM can still have non-BDI agents in the simulation, and the BDI-side can have agents that do not have a physical counterpart (such as an organisation). The framework addresses a key integration challenge of coupling event-based BDI systems, with time-stepped ABM systems. Our framework is modular and supports integration off-the-shelf BDI systems with off-the-shelf ABM systems. The framework is Open Source, and all integrations and applications are available for use by the modelling community

Computing: report leaps geographical barriers but stumbles over gender

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/62917/1/441025a.pd

Human Movement Is Both Diffusive and Directed

Understanding the influence of the built environment on human movement requires quantifying spatial structure in a general sense. Because of the difficulty of this task, studies of movement dynamics often ignore spatial heterogeneity and treat movement through journey lengths or distances alone. This study analyses public bicycle data from central London to reveal that, although journey distances, directions, and frequencies of occurrence are spatially variable, their relative spatial patterns remain largely constant, suggesting the influence of a fixed spatial template. A method is presented to describe this underlying space in terms of the relative orientation of movements toward, away from, and around locations of geographical or cultural significance. This produces two fields: one of convergence and one of divergence, which are able to accurately reconstruct the observed spatial variations in movement. These two fields also reveal categorical distinctions between shorter journeys merely serving diffusion away from significant locations, and longer journeys intentionally serving transport between spatially distinct centres of collective importance. Collective patterns of human movement are thus revealed to arise from a combination of both diffusive and directed movement, with aggregate statistics such as mean travel distances primarily determined by relative numbers of these two kinds of journeys

Predicting youth participation in urban agriculture in Malaysia: insights from the theory of planned behavior and the functional approach to volunteer motivation

This study examines factors associated with the decision of Malaysian youth to participate in a voluntary urban agriculture program. Urban agriculture has generated significant interest in developing countries to address concerns over food security, growing urbanization and employment. While an abundance of data shows attracting the participation of young people in traditional agriculture has become a challenge for many countries, few empirical studies have been conducted on youth motivation to participate in urban agriculture programs, particularly in non-Western settings. Drawing on the theories of planned behavior and the functional approach to volunteer motivation, we surveyed 890 students from a public university in Malaysia about their intention to join a new urban agriculture program. Hierarchical regression findings indicated that the strongest predictor of participation was students’ attitude toward urban agriculture, followed by subjective norms, career motives and perceived barriers to participation. The findings from this study may provide useful information to the university program planners in Malaysia in identifying mechanisms for future students’ involvement in the program

Developmental Issues in School-Based Aggression Prevention from a Social-Cognitive Perspective

Contemporary research on the development and prevention of aggressive behavior in childhood and adolescence emphasizes the importance of social-cognitive factors such as perceptual biases, problem-solving skills, and social-moral beliefs in the maintenance of aggression. Indeed, school-based social-cognitive intervention approaches have been identified as best practices by the Centers for Disease Control and Prevention. However, because child age is an important covariate of both intervention effectiveness and social-cognitive ability, school-based prevention program designers should keep in mind a number of issues identified through developmental research. In this paper, we review the social-cognitive model of aggressive behavior development as applied to prevention programming. We then discuss some of the ways in which the broader developmental research base can inform the design of aggression prevention programs.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/45098/1/10935_2005_Article_5.pd

Global challenges for seagrass conservation

Seagrasses, flowering marine plants that form underwater meadows, play a significant global role in supporting food security, mitigating climate change and supporting biodiversity. Although progress is being made to conserve seagrass meadows in select areas, most meadows remain under significant pressure resulting in a decline in meadow condition and loss of function. Effective management strategies need to be implemented to reverse seagrass loss and enhance their fundamental role in coastal ocean habitats. Here we propose that seagrass meadows globally face a series of significant common challenges that must be addressed from a multifaceted and interdisciplinary perspective in order to achieve global conservation of seagrass meadows. The six main global challenges to seagrass conservation are (1) a lack of awareness of what seagrasses are and a limited societal recognition of the importance of seagrasses in coastal systems; (2) the status of many seagrass meadows are unknown, and up-to-date information on status and condition is essential; (3) understanding threatening activities at local scales is required to target management actions accordingly; (4) expanding our understanding of interactions between the socio-economic and ecological elements of seagrass systems is essential to balance the needs of people and the planet; (5) seagrass research should be expanded to generate scientific inquiries that support conservation actions; (6) increased understanding of the linkages between seagrass and climate change is required to adapt conservation accordingly. We also explicitly outline a series of proposed policy actions that will enable the scientific and conservation community to rise to these challenges. We urge the seagrass conservation community to engage stakeholders from local resource users to international policy-makers to address the challenges outlined here, in order to secure the future of the world’s seagrass ecosystems and maintain the vital services which they supply