The recent transformation of consumer graphics (CG) cards into powerful 3D rendering processors is due in large measure to the success of game developers in delivering mass market entertainment software that feature highly immersive and captivating virtual environments. Despite this success, 3D CG application development is becoming increasingly handicapped by the inability of traditional content creation methods to keep up with the demand for content. The term content is used here to refer to any data operated on by application code that is meant for viewing, including 3D models, textures, animation sequences and maps or other data-intensive descriptions of virtual environments. Traditionally, content has been handcrafted by humans. A serious problem facing the interactive graphics software development community is how to increase the rate at which content can be produced to keep up with the increasingly rapid pace at which software for interactive applications can now be developed. Research addressing this problem centers around procedural content creation systems. By moving away from purely human content creation toward systems in which humans play a substantially less time-intensive but no less creative part in the process, procedural content creation opens new doors. From a qualitative standpoint, these types of systems will not …

Partial order planning is an important approach that solves planning problems without completely specifying the orderings between the actions in the plan. This property provides greater flexibility in executing plans; hence making the partial order planners a preferred choice over other planning methodologies. However, in order to find partially ordered plans, partial order planners perform a search in plan space rather than in space of world states and an uninformed search in plan space leads to poor efficiency. In this thesis, I discuss applying a reinforcement learning method, called First-visit Monte Carlo method, to partial order planning in order to design agents which do not need any training data or heuristics but are still able to make informed decisions in plan space based on experience. Communicating effectively with the agent is crucial in reinforcement learning. I address how this task was accomplished in plan space and the results from an evaluation of a blocks world test bed.

The major sources of power dissipation in a nanometer CMOS circuit are capacitive switching, short-circuit current, static leakage and gate oxide tunneling. However, with the aggressive scaling of technology the gate oxide direct tunneling current (gate leakage) is emerging as a prominent component of power dissipation. For sub-65 nm CMOS technology where the gate oxide (SiO2) thickness is very low, the direct tunneling current is the major form of tunneling. There are two contribution parts in this thesis: analytical modeling of behavioral level components for direct tunneling current and propagation delay, and the reduction of tunneling current during behavioral synthesis. Gate oxides of multiple thicknesses are useful in reducing the gate leakage dissipation. Analytical models from first principles to calculate the tunneling current and the propagation delay of behavioral level components is presented, which are backed by BSIM4/5 models and SPICE simulations. These components are characterized for 45 nm technology and an algorithm is provided for scheduling of datapath operations such that the overall tunneling current dissipation of a datapath circuit under design is minimal. It is observed that the oxide thickness that is being considered is very low it may not remain constant during the course of fabrication. Hence …