We complement the last three editions of the course at SIGGRAPH Asia (2015, 2016, 2018) and SIGGRAPH (2017) to make it more of a hands-on nature and include OpenISS. We explore a rapid prototyping of interactive graphical applications for stage and beyond using Jitter/Max and Processing with OpenGL, shaders, and featuring connectivity with various devices. Such rapid prototyping environment is ideal for entertainment computing, as well as for artists and live performances using real-time interactive graphics. We share the expertise we developed in connecting the real-time graphics with on-stage performance with the Illimitable Space System (ISS) v2 and its OpenISS core framework for creative near-realtime broadcasting, and the use of AI and HCI techniques in art.

This paper describes the latest version of a bi-objective multipopulation genetic algorithm (BMPGA) aiming to locate all global and local optima on a real-valued differentiable multimodal landscape. The performance of BMPGA is compared against four multimodal GAs on five multimodal functions. BMPGA is distinguished by its use of two separate but complementary fitness objectives designed to enhance the diversity of the overall population and exploration of the search space. This is coupled with a multipopulation and clustering scheme, which focuses selection within the various sub-populations and results in effective identification and retention of the optima of the target functions as well as improved exploitation within promising areas. The results of the empirical comparison provide clear evidence that supports the conclusion that BMPGA is better than the other GAs in terms of overall effectiveness, applicability, and reliability. The practical value of BMPGA has already been demonstrated in applications to multiple ellipses and elliptic objects detection in microscopic imagery.

The design of NPC (non-player character) is an analytic process. It is relying on assumptions of human game players' behavior. In practice, however, different PCs (player characters) often exhibit variable behavior, making them difficult to predicate and complicating the design process. In this paper, we describe an approach for team AI planning and learning. This approach is based on procedural knowledge and a layered multi-agent architecture. We implement real-time transfer learning and adaptive mechanism for the team of NPCs. The team can react to the human player with the tactical awareness of seasoned team behavior. Results indicate that the approach of using the hybrid of transfer learning and adaptive mechanism can improve NPCs' overall performance in real-time.

We explore the use of the developmental environment as a spatial constraint on a model of Artificial Embryogeny, applied to the growth of structural forms. A Deva model is used to translate genotype to phenotype, allowing a Genetic Algorithm to evolve Plane Trusses. Genomes are expressed in one of several developmental environments, and selected using a fitness function favouring stability, height, and distribution of pressure. Positive results are found in nearly all cases, demonstrating that environment can be used as an effective spatial constraint on development. Further experiments take genomes evolved in some environment and transplant them into different environments, or re-grow them at different phenotypic sizes; It is shown that while some genomes are highly specialized for the particular environment in which they evolved, others may be re-used in a different context without significant re-design, retaining the majority of their original utility. This strengthens the notion that growth via Artificial Embryogeny can be resistant to perturbations in environment, and that good designs may be re-used in a variety of contexts.

We present a model of artificial embryogeny, Deval, with discussion of design rationale. The motivation for an externally-evaluated test-bed for models in artificial embryogeny is discussed. We review a simple model of structural design, the plane truss. The Deval model is applied to the evolution of designs for trusses, showing that a variety of trusses satisfying distinct fitness-imposed criteria may be evolved; We evolve trusses capable of supporting external forces efficiently while either minimizing material usage or minimizing base size. Finally, we introduce a model-level perturbation, the inclusion of a seed rule, a metaphor for the initial cleavage found in real-world embryogeny. Through an empirical evaluation, we determine that the use of a seed rule is found to improve the overall quality of evolved designs, and to lessen the fitness variance between the runs.

This paper introduces two innovations into the world of multi-modal function optimization: a new multi-population genetic algorithm (GA), with two complementary fitness terms (called BMPGA); and a new similarity function that is used to decide whether two points belong to the same cluster or not, called recursive middling (RM). An empirical comparative study is carried out to provide evidence that RM is a better measure of similarity than Ursem's hill-valley (or HV) function. Another comparative study compares the performance of BMGA with our own single-fitness-term multi-population GA (SMPGA), and with Ursem's multinational GA (MGA). The results show the clear superiority of RM and BMPGA over HV and MGA, respectively. The results also point to the potential of introducing a new aspect to the field of multi-modal optimization, where various complementary (as opposed to competitive) objectives are used to maintain diversity, so the GA can find all the optima of a given fitness surface

A revolution is taking place in academic and continuing education, one that deals with the philosophy of how we teach and learn, the relationship between educators and learners, the way in which the classroom is structured, and the nature of the curriculum. This new approach, termed learner-centered education, is focused on the needs, skills and interests of the learner rather than on the organization of curriculum content. This paper describes an approach for identifying critical skills and for designing training material for learner-centered software engineering education. The approach starts from an analysis of the software developer's context of work, identifies critical skills and then associates relevant learning resources with them. The approach has been successfully used and validated in a real world-training program called PRISE that the first author developed-Programme de Reorientation des Ingenieurs Sans Emploi, a Curriculum for Retraining Unemployed Engineers in Software Engineering. The approach is also being used in some courses in the Concordia bachelor of software engineering program.

The subsumption architecture is a layered mediator invented by Rodney Brooks for behaviour-based control of robots. The layers are minimally dependent and use minimal communication. We develop an object-oriented software design for the subsumption architecture, and demonstrate that each layer can be used as a slot for a set of plug-and-play components that implement different micro-strategies for achieving a particular goal. The software architecture, and the reuse of micro-strategy components, is validated by developing truck agents within the Truckin' simulation game. Guidelines for the development of specific layers and components of a subsumption architecture are also presented.

A framework is developed in order to support the development of a family of applications. Many approaches to documenting frameworks have been tried though with different aims and audiences in mind. Of greatest utility are those aimed at reducing the learning curve for application developers. We propose the concept of a reuse case as offering a perspective of the different approaches to documenting frameworks. The categories of reuse cases are defined, and we discuss other views of reuse cases that can help to classify them.

The use case concept is a tool for capturing the requirements of a system. A single use case describes a subset of a system's functionality in terms of the interactions between the system and a set of users or actors. A use case is initiated by a particular user, and serves the purpose of delivering some meaningful unit of work, service, or value to the initiator. When capturing requirements, a use case views the system as a black box. Due to their popularity, the concept of use cases has been abused to some extent, and been applied to specifying the "requirements" of all sorts of things, such as those of a subsystem of the system architecture. Cockburn (1997) acknowledges 18 different definitions of use cases. This has created a great deal of confusion and a need for clear definitions. Just what is a "use case"? We seek to answer that question, by providing a specification of a use case and its related concepts using the Z formalism.

Understanding software documents requires the logical structure analysis of diagrammatic notations, such as data flow diagrams. A data flow diagram (DFD) represents the functional dependencies within a system: it shows how output values in a computation are derived from input values. We show how the logical structure of a DFD can be described using the formalism of Calculus of Communicating Systems (CCS). We present the process of generating the logical structure, and show how the formalism is used for deep understanding of DFDs. Using the Edinburgh Concurrency Workbench (CWB), we can use the formal description of a DFD to reason about the equivalence of two DFDs, and to simulate the behavior of a DFD.

Abstract MUSYS is a system of programs used to create electronic music at the computer studio of Electronic Music Studios, London. This paper describes the programming language employed by composers, and the implementation of its compiler and of other programs in the system. It is shown that by the use of a macrogenerator, an efficient and useful system can be built from simple software on a small computer.