http://hdl.handle.net/10464/2881 2013-06-20T03:27:32Z http://hdl.handle.net/10464/3961 Automatic evolution of conceptual building architectures Coia, Corrado This thesis describes research in which genetic programming is used to automatically evolve shape grammars that construct three dimensional models of possible external building architectures. A completely automated fitness function is used, which evaluates the three dimensional building models according to different geometric properties such as surface normals, height, building footprint, and more. In order to evaluate the buildings on the different criteria, a multi-objective fitness function is used. The results obtained from the automated system were successful in satisfying the multiple objective criteria as well as creating interesting and unique designs that a human-aided system might not discover. In this study of evolutionary design, the architectures created are not meant to be fully functional and structurally sound blueprints for constructing a building, but are meant to be inspirational ideas for possible architectural designs. The evolved models are applicable for today's architectural industries as well as in the video game and movie industries. Many new avenues for future work have also been discovered and highlighted. 2012-04-03T00:00:00Z http://hdl.handle.net/10464/3958 Formalizing affordances in situation Lenarcic, Adam The representation of a perceptual scene by a computer is usually limited to numbers representing dimensions and colours. The theory of affordances attempted to provide a new way of representing an environment, with respect to a particular agent. The view was introduced as part of an entire field of psychology labeled as 'ecological,' which has since branched into computer science through the field of robotics, and formal methods. This thesis will describe the concept of affordances, review several existing formalizations, and take a brief look at applications to robotics. The formalizations put forth in the last 20 years have no agreed upon structure, only that both the agent and the environment must be taken in relation to one another. Situation theory has also been evolving since its inception in 1983 by Barwise & Perry. The theory provided a formal way to represent any arbitrary piece of information in terms of relations. This thesis will take a toy version of situation theory published in CSLI lecture notes no. 22, and add to the given ontologies. This thesis extends the given ontologies to include specialized affordance types, and individual object types. This allows for the definition of semantic objects called environments, which support a situation and a set of affordances, and niches which refer to a set of actions for an individual. Finally, a possible way for an environment to change into a new environment is suggested via the activation of an affordance. 2012-04-03T00:00:00Z http://hdl.handle.net/10464/3957 Comparison of classification ability of hyperball algorithms to neural network and k-nearest neighbour algorithms Zibamanzar-Mofrad, Tanaby The main focus of this thesis is to evaluate and compare Hyperbalilearning algorithm (HBL) to other learning algorithms. In this work HBL is compared to feed forward artificial neural networks using back propagation learning, K-nearest neighbor and 103 algorithms. In order to evaluate the similarity of these algorithms, we carried out three experiments using nine benchmark data sets from UCI machine learning repository. The first experiment compares HBL to other algorithms when sample size of dataset is changing. The second experiment compares HBL to other algorithms when dimensionality of data changes. The last experiment compares HBL to other algorithms according to the level of agreement to data target values. Our observations in general showed, considering classification accuracy as a measure, HBL is performing as good as most ANn variants. Additionally, we also deduced that HBL.:s classification accuracy outperforms 103's and K-nearest neighbour's for the selected data sets. 2012-04-03T00:00:00Z http://hdl.handle.net/10464/3409 Evolution of architectural floor plans Flack, Robert W. J. Layout planning is a process of sizing and placing rooms (e.g. in a house) while a t t empt ing to optimize various criteria. Often the r e are conflicting c r i t e r i a such as construction cost, minimizing the distance between r e l a t ed activities, and meeting the area requirements for these activities. The process of layout planning ha s mostly been done by hand, wi th a handful of a t t empt s to automa t e the process. Thi s thesis explores some of these pa s t a t t empt s and describes several new techniques for automa t ing the layout planning process using evolutionary computation. These techniques a r e inspired by the existing methods, while adding some of the i r own innovations. Additional experimenLs are done to t e s t the possibility of allowing polygonal exteriors wi th rectilinear interior walls. Several multi-objective approaches are used to evaluate and compare fitness. The evolutionary r epr e s ent a t ion and requirements specification used provide great flexibility in problem scope and depth and is worthy of considering in future layout and design a t t empt s . The system outlined in thi s thesis is capable of evolving a variety of floor plans conforming to functional and geometric specifications. Many of the resulting plans look reasonable even when compared to a professional floor plan. Additionally polygonal and multi-floor buildings were also generated. 2011-10-13T00:00:00Z