Environmental Awareness in 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 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. Most games use agents that have a basic awareness of the player and other agents, but are still unaware of important game events or environmental conditions. This article describes an agent design that combines cellular automata for environmental modeling with influence maps for agent decision-making. The result is simple, flexible game agents that are able to respond to dynamic changes to the environment (e.g., rain or fire) while pursuing a goal.

Topological map induction using neighbourhood information of places

In topological mapping, perceptual aliasing can cause different places to appear indistinguishable to the robot. In case of severely corrupted or non-available odometry information, topological mapping is difficult as the robot is challenged with the loop-closing problem; that is to determine whether it has visited a particular place before. In this article we propose to use neighbourhood information to disambiguate otherwise indistinguishable places. Using neighbourhood information for place disambiguation is an approach that neither depends on a specific choice of sensors nor requires geometric information such as odometry. Local neighbourhood information is extracted from a sequence of observations of visited places. In experiments using either sonar or visual observations from an indoor environment the benefits of using neighbourhood clues for the disambiguation of otherwise identical vertices are demonstrated. Over 90% of the maps we obtain are isomorphic with the ground truth. The choice of the robot’s sensors does not impact the results of the experiments much.

A semi-local method for iterative depth-map refinement

We present an iterative hierarchical algorithm for multi-view stereo. The algorithm attempts to utilise as much contextual information as is available to compute highly accurate and robust depth maps. There are three novel aspects to the approach: 1) firstly we incrementally improve the depth fidelity as the algorithm progresses through the image pyramid; 2) secondly we show how to incorporate visual hull information (when available) to constrain depth searches; and 3) we show how to simultaneously enforce the consistency of the depth-map by continual comparison with neighbouring depth-maps. We show that this approach produces highly accurate depth-maps and, since it is essentially a local method, is both extremely fast and simple to implement.

Deep Raman spectroscopy for the non-invasive standoff detection of concealed chemical threat agents

Deep Raman spectroscopy has been utilized for the standoff detection of concealed chemical threat agents from a distance of 15 meters under real life background illumination conditions. By using combined time and space resolved measurements, various explosive precursors hidden in opaque plastic containers were identified non-invasively. Our results confirm that combined time and space resolved Raman spectroscopy leads to higher selectivity towards the sub-layer over the surface layer as well as enhanced rejection of fluorescence from the container surface when compared to standoff spatially offset Raman spectroscopy. Raman spectra that have minimal interference from the packaging material and good signal-to-noise ratio were acquired within 5 seconds of measurement time. A new combined time and space resolved Raman spectrometer has been designed with nanosecond laser excitation and gated detection, making it of lower cost and complexity than picosecond-based laboratory systems.

Learning and acting in project situations through a meta-method (MAP) a case study : contextual and situational approach for project management governance in management education

The paper introduces the underlying principles and the general features of a meta-method (MAP method) developed as part of and used in various research, education and professional development programmes at ESC Lille. This method aims at providing effective and efficient structure and process for acting and learning in various complex, uncertain and ambiguous managerial situations (projects, programmes, portfolios). The paper is developed around three main parts. First, I suggest revisiting the dominant vision of the project management knowledge field, based on the assumptions they are not addressing adequately current business and management contexts and situations, and that competencies in management of entrepreneurial activities are the sources of creation of value for organisations. Then, grounded on the former developments, I introduce the underlying concepts supporting MAP method seen as a ‘convention generator’ and how this meta method inextricably links learning and practice in addressing managerial situations. Finally, I briefly describe an example of application, illustrating with a case study how the method integrates Project Management Governance, and give few examples of use in Management Education and Professional Development.

Learning and acting in project situations through a meta-method (MAP) : a case study : contextual and situational approach for project management governance in management education

The paper introduces the underlying principles and the general features of a meta-method (MAP method – Management & Analysis of Projects) developed as part of and used in various research, education and professional development programmes at ESC Lille. This method aims at providing effective and efficient structure and process for acting and learning in various complex, uncertain and ambiguous managerial situations (projects, programmes, portfolios). The paper is organized in three parts. In a first part, I propose to revisit the dominant vision of the project management knowledge field, based on the assumptions they are not addressing adequately current business and management contexts and situations, and that competencies in management of entrepreneurial activities are the sources of creation of value for organisations. Then, grounded on the new suggested perspective, the second part presents the underlying concepts supporting MAP method seen as a ‘convention generator' and how this meta-method inextricably links learning and practice in addressing managerial situations. The third part describes example of application, illustrating with a brief case study how the method integrates Project Management Governance, and gives few examples of use in Management Education and Professional Development.

Adaptive bilateral filtering using saliency map for deblocking low bit rate videos

This paper proposes a novel approach to video deblocking which performs perceptually adaptive bilateral filtering by considering color, intensity, and motion features in a holistic manner. The method is based on bilateral filter which is an effective smoothing filter that preserves edges. The bilateral filter parameters are adaptive and avoid over-blurring of texture regions and at the same time eliminate blocking artefacts in the smooth region and areas of slow motion content. This is achieved by using a saliency map to control the strength of the filter for each individual point in the image based on its perceptual importance. The experimental results demonstrate that the proposed algorithm is effective in deblocking highly compressed video sequences and to avoid over-blurring of edges and textures in salient regions of image.

CAT-SLAM : probabilistic localisation and mapping using a continuous appearance-based trajectory

This paper describes a new system, dubbed Continuous Appearance-based Trajectory Simultaneous Localisation and Mapping (CAT-SLAM), which augments sequential appearance-based place recognition with local metric pose filtering to improve the frequency and reliability of appearance-based loop closure. As in other approaches to appearance-based mapping, loop closure is performed without calculating global feature geometry or performing 3D map construction. Loop-closure filtering uses a probabilistic distribution of possible loop closures along the robot’s previous trajectory, which is represented by a linked list of previously visited locations linked by odometric information. Sequential appearance-based place recognition and local metric pose filtering are evaluated simultaneously using a Rao–Blackwellised particle filter, which weights particles based on appearance matching over sequential frames and the similarity of robot motion along the trajectory. The particle filter explicitly models both the likelihood of revisiting previous locations and exploring new locations. A modified resampling scheme counters particle deprivation and allows loop-closure updates to be performed in constant time for a given environment. We compare the performance of CAT-SLAM with FAB-MAP (a state-of-the-art appearance-only SLAM algorithm) using multiple real-world datasets, demonstrating an increase in the number of correct loop closures detected by CAT-SLAM.

Controlling Minimally-Actuated Vehicles for Applications in Ocean Observation

Establishing a persistent presence in the ocean with an AUV to observe temporal variability of large-scale ocean processes requires a unique sensor platform. In this paper, we propose a strategy that utilizes ocean model predictions to increase the autonomy and control of Lagrangian or profiling floats for precisely this purpose. An A* planner is applied to a local controllability map generated from predictions of ocean currents to compute a path between prescribed waypoints that has the highest likelihood of successful execution. The control to follow the planned path is computed by use of a model predictive controller. This controller is designed to select the best depth for the vehicle to exploit ambient currents to reach the goal waypoint. Mission constraints are employed to simulate a practical data collection mission. Results are presented in simulation for a mission off the coast of Los Angeles, CA USA, and show surprising results in the ability of a Lagrangian float to reach a desired location.

Do anti-inflammatory agents promote linear ablation lesion discontinuities? : an electrophysiological examination

Background: Catheter ablation for atrial fibrillation (AF) is more efficacious than antiarrhythmic therapy. Post ablation recurrences reduce ablation effectiveness and are contributed by lesion discontinuity in the fibrotic linear ablation lesions. The anti-fibrotic role of statins in reducing AF is being assessed in current trials. By reducing the chronic pathological fibrosis that occurs in AF they may reduce AF. However if statins also have an effect on the acute therapeutic fibrosis of an ablation, this could exacerbate lesion discontinuity and AF recurrence. We tested the hypothesis that statins attenuate ablation lesion continuity in a recognised pig atrial linear ablation model. Aims: To assess whether Atorvastatin diminishes the bi-directional conduction block produced by a linear atrial ablation lesion. Methods: Sixteen pigs were randomised to statin (n=8) or placebo (n=8) with drug pre-treatment for 3 days and a further 4 weeks. At initial electrophysiological study (EPS1) 3D right atrium (RA) mapping and a vertical ablation linear lesion in the posterior RA with bidirectional conduction block were completed (Gepstein Circ 1999). Follow-up electrophysiological assessment (EPS2) at 28 days assessed bidirectional conduction block maintenance. Results: Data of 15/16 (statin=7) pigs were analysed. Mean lesion length was 3.7 ± 0.8cm with a mean of 17.9 ± 5.7 lesion applications. Bi-directional conduction block was confirmed in 15/15 pigs (100%) at EPS1 and EPS2. Conclusions: Atorvastatin did not affect ablation lesion continuity in this pig atrial linear ablation model. If patients are on long-term statins for AF reduction, periablation cessation is probably not necessary.

OpenFABMAP : an open source toolbox for appearance-based loop closure detection

Appearance-based loop closure techniques, which leverage the high information content of visual images and can be used independently of pose, are now widely used in robotic applications. The current state-of-the-art in the field is Fast Appearance-Based Mapping (FAB-MAP) having been demonstrated in several seminal robotic mapping experiments. In this paper, we describe OpenFABMAP, a fully open source implementation of the original FAB-MAP algorithm. Beyond the benefits of full user access to the source code, OpenFABMAP provides a number of configurable options including rapid codebook training and interest point feature tuning. We demonstrate the performance of OpenFABMAP on a number of published datasets and demonstrate the advantages of quick algorithm customisation. We present results from OpenFABMAP’s application in a highly varied range of robotics research scenarios.

Proteasome inhibitors as anti-cancer agents

The ubiquitin (Ub)-proteasome pathway is the major nonlysosomal pathway of proteolysis in human cells and accounts for the degradation of most short-lived, misfolded or damaged proteins. This pathway is important in the regulation of a number of key biological regulatory mechanisms. Proteins are usually targeted for proteasome-mediated degradation by polyubiquitinylation, the covalent addition of multiple units of the 76 amino acid protein Ub, which are ligated to 1-amino groups of lysine residues in the substrate. Polyubiquitinylated proteins are degraded by the 26S proteasome, a large, ATP-dependent multicatalytic protease complex, which also regenerates monomeric Ub. The targets of this pathway include key regulators of cell proliferation and cell death. An alternative form of the proteasome, termed the immunoproteasome, also has important functions in the generation of peptides for presentation by MHC class I molecules. In recent years there has been a great deal of interest in the possibility that proteasome inhibitors, through elevation of the levels of proteasome targets, might prove useful as a novel class of anti-cancer drugs. Here we review the progress made to date in this area and highlight the potential advantages and weaknesses of this approach.

Does section 420A impose ‘strict liability’ upon controllers for acts or omissions of agents and experts?

This article addresses in depth the question of whether section 420A of the Corporations Act 2001 (Cth) imposes ‘strict liability’ upon a controller for the failure of an agent or expert to take reasonable care. The weight of existing authority appears to suggest that controllers are liable under s 420A for the carelessness of their agents or expert advisers. However, a closer analysis of the text of the provision and relevant Australian and UK case law demonstrates that this aspect of the statutory construction of s 420A remains very much an open question. This article ultimately contends for a construction of s 420A which requires a controller to adequately supervise and scrutinise, but which does not render a blameless controller strictly liable for all careless acts and omissions of agents and expert advisers.

Control and application of minimally-actuated underwater vehicles

Establishing a persistent presence in the ocean with an Autonomous Underwater Vehicle capable of observing temporal variability of large-scale ocean processes requires a unique sensor platform. In this paper, we examine the utility of Lagrangian profiling floats for such extended deployments. We propose a strategy that utilizes ocean model predictions to facilitate a basic level of autonomy to achieve general control of this minimally-actuated underwater vehicle. We extend experimentally validated techniques for utilising ocean current models to control under-actuated autonomous underwater vehicles by presenting this investigation into the application of these methods on profiling floats. With the appropriate vertical actuation, and utilising spatiotemporal variations in water speed and direction, we show that broad controllability results can be met. First, we apply an A* planner to a local controllability map generated from predictions of ocean currents. This computes a path between start and goal waypoints that has the highest likelihood of successful execution over a given duration. The computed depth plan is generated with a model predictive controller, and selects the depths for the vehicle so that ambient currents guide it toward the goal. Mission constraints are included to simulate and motivate a practical data collection mission. Results are presented in simulation for a mission off the coast of Los Angeles, CA USA, that show surprising results in the ability of a drifting vehicle to maintain a prescribed course and reach a desired location.

Beyond here-and-now : extending shared physical experiences to shared conceptual experiences

For robots to use language effectively, they need to refer to combinations of existing concepts, as well as concepts that have been directly experienced. In this paper, we introduce the term generative grounding to refer to the establishment of shared meaning for concepts referred to using relational terms. We investigated a spatial domain, which is both experienced and constructed using mobile robots with cognitive maps. The robots, called Lingodroids, established lexicons for locations, distances, and directions through structured conversations called where-are-we, how-far, what-direction, and where-is-there conversations. Distributed concept construction methods were used to create flexible concepts, based on a data structure called a distributed lexicon table. The lexicon was extended from words for locations, termed toponyms, to words for the relational terms of distances and directions. New toponyms were then learned using these relational operators. Effective grounding was tested by using the new toponyms as targets for go-to games, in which the robots independently navigated to named locations. The studies demonstrate how meanings can be extended from grounding in shared physical experiences to grounding in constructed cognitive experiences, giving the robots a language that refers to their direct experiences, and to constructed worlds that are beyond the here-and-now.