Abstract:
There are many situations in which it would be beneficial for a robot to have predictive abilities similar to those of rational humans. Some of these situations include collaborative robots, robots in adversarial situations, and for dynamic obstacle avoidance. This paper presents an approach to modeling behaviors of dynamic agents in order to empower robots with the ability to predict the agent's actions and identify the behavior the agent is executing in real time. The method of behavior modeling implemented uses hidden Markov models (HMMs) to model the unobservable states of the dynamic agents. The background and theory of the behavior modeling is presented. Experimental results of realistic simulations of a robot predicting the behaviors and actions of a dynamic agent in a static environment are presented.

Abstract:
This paper describes a novel method for allowing an autonomous ground vehicle to predict the intent of other agents in an urban environment. This method, termed the cognitive driving framework, models both the intent and the potentially false beliefs of an obstacle vehicle. By modeling the relationships between these variables as a dynamic Bayesian network, filtering can be performed to calculate the intent of the obstacle vehicle as well as its belief about the environment. This joint knowledge can be exploited to plan safer and more efficient trajectories when navigating in an urban environment. Simulation results are presented that demonstrate the ability of the proposed method to calculate the intent of obstacle vehicles as an autonomous vehicle navigates a road intersection such that preventative maneuvers can be taken to avoid imminent collisions.

Abstract:
We show that reasonably well behaved 3d and 4D TQFts must contain certain algebraic structures. In 4D, we find both Hopf categories and trialgebras.

Abstract:
We study the relaxation response of a social system after endogenous and exogenous bursts of activity using the time-series of daily views for nearly 5 million videos on YouTube. We find that most activity can be described accurately as a Poisson process. However, we also find hundreds of thousands of examples in which a burst of activity is followed by an ubiquitous power-law relaxation governing the timing of views. We find that these relaxation exponents cluster into three distinct classes, and allow for the classification of collective human dynamics. This is consistent with an epidemic model on a social network containing two ingredients: A power law distribution of waiting times between cause and action and an epidemic cascade of actions becoming the cause of future actions. This model is a conceptual extension of the fluctuation-dissipation theorem to social systems, and provides a unique framework for the investigation of timing in complex systems.

Abstract:
The purpose of this note is to make several advances in the interpretation of the balanced state sum model by Barrett and Crane in gr-qc/9709028 as a quantum theory of gravity. First, we outline a shortcoming of the definition of the model in pointed out to us by Barrett and Baez in private communication, and explain how to correct it. Second, we show that the classical limit of our state sum reproduces the Einstein-Hilbert lagrangian whenever the term in the state sum to which it is applied has a geometrical interpretation. Next we outline a program to demonstrate that the classical limit of the state sum is in fact dominated by terms with geometrical meaning. This uses in an essential way the alteration we have made to the model in order to fix the shortcoming discussed in the first section. Finally, we make a brief discussion of the Minkowski signature version of the model.

Abstract:
This is intended as a self-contained introduction to the representation theory developed in order to create a Poincare 2-category state sum model for Quantum Gravity in 4 dimensions. We review the structure of a new representation 2-category appropriate to Lie 2-group symmetries and discuss its application to the problem of finding a state sum model for Quantum Gravity. There is a remarkable richness in its details, reflecting some desirable characteristics of physical 4-dimensionality. We begin with a review of the method of orbits in Geometric Quantization, as an aid to the intuition that the geometric picture unfolded here may be seen as a categorification of this process.

Abstract:
Using the theory of measurable categories developped by Yetter in work in preparation, we provide a notion of representations of 2-groups more well-suited to physically and geometrically interesting examples than that proposed in unpublished work of Barrett and Mackaay using 2-VECT of Kapranov and Voevodsky. Using this theory we sketch a 2-categorical approach to the state-sum model for Lorentzian quantum gravity proposed in by the authors in previous work and suggest state-integral constructions for 4-manifold invariants.

Abstract:
Cyber-physical systems (CPS) represent a
class of complex engineered systems where functionality and behavior emerge
through the interaction between the computational and physical domains.
Simulation provides design engineers with quick and accurate feedback on the
behaviors generated by their designs. However, as systems become more complex,
simulating their behaviors becomes computation all complex. But, most modern
simulation environments still execute on a single thread, which does not take
advantage of the processing power available on modern multi-core CPUs. This
paper investigates methods to partition and simulate differential
equation-based models of cyber-physical systems using multiple threads on
multi-core CPUs that can share data across threads. We describe model
partitioning methods using fixed step and variable step numerical in-tegration
methods that consider the multi-layer cache structure of these CPUs to avoid
simulation performance degradation due to cache conflicts. We study the
effectiveness of each parallel simu-lation algorithm by calculating the
relative speedup compared to a serial simulation applied to a series of large
electric circuit models. We also develop a series of guidelines for maximizing
performance when developing parallel simulation software intended for use on
multi-core CPUs.

Abstract:
We give an overview of the current issues in early universe cosmology and consider the potential resolution of these issues in an as yet nascent spin foam cosmology. The model is the Barrett-Crane Model for quantum gravity along with a generalization of manifold complexes to complexes including conical singularities.

Abstract:
This paper presents the design, analysis, and experimental validation of the passive case of a variable stiffness suspension system. The central concept is based on a recently designed variable stiffness mechanism. It consists of a horizontal control strut and a vertical strut. The main idea is to vary the load transfer ratio by moving the location of the point of attachment of the vertical strut to the car body. This movement is controlled passively using the horizontal strut. The system is analyzed using an L2-gain analysis based on the concept of energy dissipation. The analyses, simulation, and experimental results show that the variable stiffness suspension achieves better performance than the constant stiffness counterpart. The performance criteria used are; ride comfort, characterized by the car body acceleration, suspension deflection, and road holding, characterized by tire deflection.