Applications of CSP solving in computer games (camera control)

While camera control systems of commercial 3D games have improved greatly in recent years, they are not as fully developed as are other game components such as graphics and physics engines. Bourne and Sattar (2006) have proposed a reactive constraint based third person perspective camera control system. We have extended the capability of their system to handle occlusion while following the main character, and have used camera cuts to find appropriate camera positions for a few difficult situations. We have developed a reactive constraint based third person perspective chase camera control system to follow a character in a 3D environment. The camera follows the character from (near) optimal positions defined by a camera profile. The desired values of the height and distance constraints of the camera profile are changed appropriately whenever the character enters a semi-enclosed or an enclosed area, and the desired value of the orientation constraint of the camera profile is changed incrementally whenever theoptimal camera view is obstructed. Camera cuts are used whenever the main character backs up to a wall or any other obstructions, or comes out of a semi-enclosed or an enclosed area. Two auxiliary cameras to observe the main camera positions from top and side views have been added. The chase camera control system achieved real-time performance while following the main character in a typical 3D environment, and maintained an optimal view based on a user specified/selected camera profile

CASP Solutions for Planning in Hybrid Domains

CASP is an extension of ASP that allows for numerical constraints to be added in the rules. PDDL+ is an extension of the PDDL standard language of automated planning for modeling mixed discrete-continuous dynamics. In this paper, we present CASP solutions for dealing with PDDL+ problems, i.e., encoding from PDDL+ to CASP, and extensions to the algorithm of the EZCSP CASP solver in order to solve CASP programs arising from PDDL+ domains. An experimental analysis, performed on well-known linear and non-linear variants of PDDL+ domains, involving various configurations of the EZCSP solver, other CASP solvers, and PDDL+ planners, shows the viability of our solution.Comment: Under consideration in Theory and Practice of Logic Programming (TPLP

A Constraint Solver based on Abstract Domains

International audienceIn this article, we apply techniques from Abstract Interpretation (a general theory of semantic abstractions) to Constraint Programming (which aims at solving hard combinatorial problems with a generic framework based on first-order logics). We highlight some links and differences between these fields: both compute fixpoints by iteration but employ different extrapolation and refinement strategies; moreover, consistencies in Constraint Programming can be mapped to non-relational abstract domains. We then use these correspondences to build an abstract constraint solver that leverages abstract interpretation techniques (such as relational domains) to go beyond classic solvers. We present encouraging experimental results obtained with our prototype implementation

Automotive Threat Assessment Design for Combined Braking and Steering Maneuvers

The active safety systems available on the passenger cars market today, automatically deploy automated safety interventions in situations where the driver is in need of assistance. In this paper, we consider the process of determining whether such interventions are needed. In particular, we design a threat assessment method which evaluates the risk that the vehicle will either leave the road or its maneuverability will be significantly reduced within a finite time horizon. The proposed threat assessment method accounts for combined braking and steering maneuvers, which results in a nonlinear dynamical vehicle behavior. We formulate the threat assessment problem as a nonconvex constraint satisfaction problem and implement an algorithm that solves it through interval-based consistency techniques. Experimental validation of the proposed approach indicates that constraint violation can be predicted, while avoiding the detection of false threats

Virtual camera selection using a semiring constraint satisfaction approach

Players and viewers of three-dimensional computer generated games and worlds view renderings from the viewpoint of a virtual camera. As such, determining a good view of the scene is important to present a good game or three-dimensional world. Previous research has developed technologies to nd good positions for the virtual camera, but little work has been done to automatically select between multiple virtual cameras, similar to a human director at a sporting event. This thesis describes a software tool to select among camera feeds from multiple virtual cameras in a virtual environment using semiring-based constraint satisfaction techniques (SCSP), a soft constraint approach. The system encodes a designer's preferences, and selects the best camera feed even in over-constrained or under-constrained environments. The system functions in real time for dynamic scenes using only current information (i.e. no prediction). To reduce the camera selection time the SCSP evaluation can be cached and converted to native code. This SCSP approach is implemented in two virtual environments: a virtual hockey game using a spectator viewpoint, and a virtual 3D maze game using a third person perspective. Comparisons against hard constraints are made using constraint satisfaction problems

Novel Techniques for Secure Use of Public Cloud Computing Resources

The federal government has an expressed interest in moving data and services to third party service providers in order to take advantage of the flexibility, scalability, and potential cost savings. This approach is called cloud computing. The thesis for this research is that efficient techniques exist to support the secure use of public cloud computing resources by a large, federated enterprise. The primary contributions of this research are the novel cryptographic system MA-AHASBE (Multi-Authority Anonymous Hierarchical Attribute-Set Based Encryption), and the techniques used to incorporate MA-AHASBE in a real world application. Performance results indicate that while there is a cost associated with enforcing the suggested security model, the cost is not unreasonable and the benefits in security can be significant. The contributions of this research give the DoD additional tools for supporting the mission while taking advantage of the cost efficient public cloud computing resources that are becoming widely available

Informed selection and use of training examples for knowledge refinement.

Knowledge refinement tools seek to correct faulty rule-based systems by identifying and repairing faults indicated by training examples that provide evidence of faults. This thesis proposes mechanisms that improve the effectiveness and efficiency of refinement tools by the best use and selection of training examples. The refinement task is sufficiently complex that the space of possible refinements demands a heuristic search. Refinement tools typically use hill-climbing search to identify suitable repairs but run the risk of getting caught in local optima. A novel contribution of this thesis is solving the local optima problem by converting the hill-climbing search into a best-first search that can backtrack to previous refinement states. The thesis explores how different backtracking heuristics and training example ordering heuristics affect refinement effectiveness and efficiency. Refinement tools rely on a representative set of training examples to identify faults and influence repair choices. In real environments it is often difficult to obtain a large set of training examples, since each problem-solving task must be labelled with the expert's solution. Another novel aspect introduced in this thesis is informed selection of examples for knowledge refinement, where suitable examples are selected from a set of unlabelled examples, so that only the subset requires to be labelled. Conversely, if a large set of labelled examples is available, it still makes sense to have mechanisms that can select a representative set of examples beneficial for the refinement task, thereby avoiding unnecessary example processing costs. Finally, an experimental evaluation of example utilisation and selection strategies on two artificial domains and one real application are presented. Informed backtracking is able to effectively deal with local optima by moving search to more promising areas, while informed ordering of training examples reduces search effort by ensuring that more pressing faults are dealt with early on in the search. Additionally, example selection methods achieve similar refinement accuracy with significantly fewer examples

Smart Energy and Intelligent Transportation Systems

With the Internet of Things and various information and communication technologies, a city can manage its assets in a smarter way, constituting the urban development vision of a smart city. This facilitates a more efficient use of physical infrastructure and encourages citizen participation. Smart energy and smart mobility are among the key aspects of the smart city, in which the electric vehicle (EV) is believed to take a key role. EVs are powered by various energy sources or the electricity grid. With proper scheduling, a large fleet of EVs can be charged from charging stations and parking infrastructures. Although the battery capacity of a single EV is small, an aggregation of EVs can perform as a significant power source or load, constituting a vehicle-to-grid (V2G) system. Besides acquiring energy from the grid, in V2G, EVs can also support the grid by providing various demand response and auxiliary services. Thanks to this, we can reduce our reliance on fossil fuels and utilize the renewable energy more effectively. This Special Issue “Smart Energy and Intelligent Transportation Systems” addresses existing knowledge gaps and advances smart energy and mobility. It consists of five peer-reviewed papers that cover a range of subjects and applications related to smart energy and transportation

Cavum Septum Pellucidum and Absence of the Adhesio Interthalamica in Frontotemporal dementia and Alzheimer’s disease: Prevalence and associations with clinical features

Large Cavum Septum Pellucidum (CSP) and Absence of the Adhesio Interthalamica (AAI) are midline brain abnormalities that are more frequent in individuals with mental illness, particularly in schizophrenia spectrum disorders, where they have been associated with psychosis and negative features such as apathy and amotivation. Psychiatric features are also observed in the dementias and whether these are associated with midline brain abnormalities has not been investigated. This project investigated the prevalence of CSP and AAI in Alzheimer’s Dementia (AD) and behavioural-variant frontotemporal dementia (bvFTD), given patients with both dementias may present with early psychotic features. To investigate this, a retrospective case control study was conducted, with patients with AD, bvFTD and controls recruited from FRONTIER, the Frontotemporal Dementia Research clinic at the Brain and Mind Centre, University of Sydney. Ninety-three individuals diagnosed with AD (n=47) and bvFTD (n=46) and 81 age- and sex- matched controls were included. CSP and AAI were not more prevalent in dementia than controls. However, the anteroposterior length of the CSP was significantly longer in AD and bvFTD (mean CSP length in AD, 4.29 (+/-2)mm; 4.17 (+/-1.97)mm for bvFTD and 3.17(+/-1.58)mm for controls, p=.02). Large CSP (6mm or more) and AAI were more common in men, but sex did not explain the association of longer CSP with AD and bvFTD. Contrary to the hypotheses, presence of CSP and AAI, as well as length of CSP, did not correlate convincingly with any psychiatric scores. Following this, nine patients with AD or bvFTD and large CSP of 6mm were described. In conclusion, this study showed a longer CSP in AD and bvFTD compared to controls, but this was not explained by neuropsychiatric features. This study was limited by a small sample size and the low frequency of psychosis in the dementia cases. Future studies will benefit by including volumetric MRI and longitudinal design