Combining influence maps and cellular automata for reactive game agents

Agents make up an important part of game worlds, ranging from the characters and monsters that live in the world to the armies that the player controls. Despite their importance, agents in current games rarely display an awareness of their environment or react appropriately, which severely detracts from the believability of the game. Some games have included agents with a basic awareness of other agents, but they are still unaware of important game events or environmental conditions. This paper presents an agent design we have developed, which combines cellular automata for environmental modeling with influence maps for agent decision-making. The agents were implemented into a 3D game environment we have developed, the EmerGEnT system, and tuned through three experiments. The result is simple, flexible game agents that are able to respond to natural phenomena (e.g. rain or fire), while pursuing a goal.

The PSS : From Flat Maps to Layered Perspectives - the contribution of the Airport Metropolis Planning Support System (PSS) to sub-regional planning in the Brisbane Airport case environment

Conventional planning and decision making, with its sectoral and territorial emphasis and flat-map based processes are no longer adequate or appropriate for the increased complexity confronting airport/city interfaces. These crowed and often contested governance spaces demand a more iterative and relational planning and decision-making approach. Emergent GIS based planning and decision-making tools provide a mechanism which integrate and visually display an array of complex data, frameworks and scenarios/expectations, often in ‘real time’ computations. In so doing, these mechanisms provide a common ground for decision making and facilitate a more ‘joined-up’ approach to airport/city planning. This paper analyses the contribution of the Airport Metropolis Planning Support System (PSS) to sub-regional planning in the Brisbane Airport case environment.

Which way from here? The spatiality of maps & navigation in first-person single-player video games

Player experience of spatiality in first-person, single-player games is informed by the maps and navigational aids provided by the game. This project uses textual analysis to examine the way these maps and navigational aids inform the experience of spatiality in Fallout 3, BioShock and BioShock 2. Spatiality is understood as trialectic, incorporating perceived, conceived and lived space, drawing on the work of Henri Lefebvre and Edward Soja. The most prominent elements of the games’ maps and navigational aids are analysed in terms of how they inform players’ experience of the games’ spaces. In particular this project examines the in-game maps these games incorporate, the waypoint navigation and fast-travel systems in Fallout 3, and the guide arrow and environmental cues in the BioShock games.

Using incomplete online metric maps for topological exploration with the Gap Navigation Tree

This paper presents a general, global approach to the problem of robot exploration, utilizing a topological data structure to guide an underlying Simultaneous Localization and Mapping (SLAM) process. A Gap Navigation Tree (GNT) is used to motivate global target selection and occluded regions of the environment (called “gaps”) are tracked probabilistically. The process of map construction and the motion of the vehicle alters both the shape and location of these regions. The use of online mapping is shown to reduce the difficulties in implementing the GNT.

Development priority zoning (DPZ)-led scenario simulation for regional land use change : the case of Suichang County, China

China has experienced an extraordinary level of economic development since the 1990s, following excessive competition between different regions. This has resulted in many resource and environmental problems. Land resources, for example, are either abused or wasted in many regions. The strategy of development priority zoning (DPZ), proposed by the Chinese National 11th Five-Year Plan, provides an opportunity to solve these problems by coordinating regional development and protection. In line with the rational utilization of land, it is proposed that the DPZ strategy should be integrated with regional land use policy. As there has been little research to date on this issue, this paper introduces a system dynamic (SD) model for assessing land use change in China led by the DPZ strategy. Land use is characterized by the prioritization of land development, land utilization, land harness and land protection (D-U-H-P). By using the Delphi method, a corresponding suitable prioritization of D-U-H-P for the four types of DPZ, including optimized development zones (ODZ), key development zones (KDZ), restricted development zones (RDZ), and forbidden development zones (FDZ) are identified. Suichang County is used as a case study in which to conduct the simulation of land use change under the RDZ strategy. The findings enable a conceptualization to be made of DPZ-led land use change and the identification of further implications for land use planning generally. The SD model also provides a potential tool for local government to combine DPZ strategy at the national level with land use planning at the local level.

New maps of learning for quality art education : what pre-service teachers should learn and be able to do

It would be a rare thing to visit an early years setting or classroom in Australia that does not display examples of young children’s artworks. This practice serves to give schools a particular ‘look’, but is no guarantee of quality art education. The Australian National Review of Visual Arts Education (NRVE) (2009) has called for changes to visual art education in schools. The planned new National Curriculum includes the arts (music, dance, drama, media and visual arts) as one of the five learning areas. Research shows that it is the classroom teacher that makes the difference, and teacher education has a large part to play in reforms to art education. This paper provides an account of one foundation unit of study (Unit 1) for first year university students enrolled in a 4-year Bachelor degree program who are preparing to teach in the early years (0–8 years). To prepare pre-service teachers to meet the needs of children in the 21st century, Unit 1 blends old and new ways of seeing art, child and pedagogy. Claims for the effectiveness of this model are supported with evidence-based research, conducted over the six years of iterations and ongoing development of Unit 1.

Building Large Scale Traversability Maps Using Vehicle Experience

Traversability maps are a global spatial representation of the relative difficulty in driving through a local region. These maps support simple optimisation of robot paths and have been very popular in path planning techniques. Despite the popularity of these maps, the methods for generating global traversability maps have been limited to using a-priori information. This paper explores the construction of large scale traversability maps for a vehicle performing a repeated activity in a bounded working environment, such as a repeated delivery task.We evaluate the use of vehicle power consumption, longitudinal slip, lateral slip and vehicle orientation to classify the traversability and incorporate this into a map generated from sparse information.

Physical and linkage maps for Drosophila serrata, a model species for studies of clinal adaptation and sexual selection

Drosophila serrata is a member of the montium group, which contains more than 98 species and until recently was considered a subgroup within the melanogaster group. This Drosophila species is an emerging model system for evolutionary quantitative genetics and has been used in studies of species borders, clinal variation and sexual selection. Despite the importance of D. serrata as a model for evolutionary research, our poor understanding of its genome remains a significant limitation. Here, we provide a first-generation gene-based linkage map and a physical map for this species. Consistent with previous studies of other drosophilids we observed strong conservation of genes within chromosome arms homologous with D. melanogaster but major differences in within-arm synteny. These resources will be a useful complement to ongoing genome sequencing efforts and QTL mapping studies in this species

One-year delayed effect of fog on malaria transmission : a time-series analysis in the rain forest area of Mengla County, south-west China

Background: Malaria is a major public health burden in the tropics with the potential to significantly increase in response to climate change. Analyses of data from the recent past can elucidate how short-term variations in weather factors affect malaria transmission. This study explored the impact of climate variability on the transmission of malaria in the tropical rain forest area of Mengla County, south-west China. Methods: Ecological time-series analysis was performed on data collected between 1971 and 1999. Auto-regressive integrated moving average (ARIMA) models were used to evaluate the relationship between weather factors and malaria incidence. Results: At the time scale of months, the predictors for malaria incidence included: minimum temperature, maximum temperature, and fog day frequency. The effect of minimum temperature on malaria incidence was greater in the cool months than in the hot months. The fog day frequency in October had a positive effect on malaria incidence in May of the following year. At the time scale of years, the annual fog day frequency was the only weather predictor of the annual incidence of malaria. Conclusion: Fog day frequency was for the first time found to be a predictor of malaria incidence in a rain forest area. The one-year delayed effect of fog on malaria transmission may involve providing water input and maintaining aquatic breeding sites for mosquitoes in vulnerable times when there is little rainfall in the 6-month dry seasons. These findings should be considered in the prediction of future patterns of malaria for similar tropical rain forest areas worldwide.

Uninav : a context-aware mobile application for university campus maps

The smart phones we carry with us are becoming ubiquitous with everyday life and the sensing capabilities of these devices allow us to provide context-aware services. In this paper, we discuss the development of UniNav, a context-aware mobile application that delivers personalised campus maps for universities. The application utilises university students’ details to provide information and services that are relevant and important to them. It helps students to navigate within the campus and become familiar with their university environment quickly. A study was undertaken to evaluate the acceptability and usefulness of the campus map, as well as the impact on a users’ navigation efficiency by utilising the personal and environmental contexts. The result indicates the integration of personal and environmental contexts on digital maps can improve its usefulness and navigation efficiency.

Context-aware device self-configuration using self-organizing maps

Modern mobile computing devices are versatile, but bring the burden of constant settings adjustment according to the current conditions of the environment. While until today, this task has to be accomplished by the human user, the variety of sensors usually deployed in such a handset provides enough data for autonomous self-configuration by a learning, adaptive system. However, this data is not fully available at certain points in time, or can contain false values. Handling potentially incomplete sensor data to detect context changes without a semantic layer represents a scientific challenge which we address with our approach. A novel machine learning technique is presented - the Missing-Values-SOM - which solves this problem by predicting setting adjustments based on context information. Our method is centered around a self-organizing map, extending it to provide a means of handling missing values. We demonstrate the performance of our approach on mobile context snapshots, as well as on classical machine learning datasets.