In this paper, we consider constrained noncooperativeN -person stochastic games with discounted cost criteria. The state space is assumed to be countable and the action sets are compact metric spaces. We present three main results. The first concerns the sensitivity or approximation of constrained games. The second shows the existence of Nash equilibria for constrained games with a finite state...

This paper proposes a novel algorithm for solving NP-hard constrained discrete minimization problems whose unconstrained versions are solvable in polynomial time such as constrained submodular function minimization. Applications of our algorithm include constrained MAP inference in Markov Random Fields, and energy minimization in various computer vision problems. Our algorithm assumes the exist...

We study geometry of the phase space for finite dimensional dynamical systems with degenerate Lagrangians. The Lagrangian and Hamiltonian constraint formalisms are treated as the different local-coordinate pictures of the same invariant procedure. The invariant description is given in terms of geometrical objects associated with the structure of foliation on the phase space.

Constrained dynamics on finite-dimensional trial manifolds of quantum state vectors appears in time-dependent variational calculations. This work presents a requantization method, by which properties of the exact eigenstates can be retrieved from the phase portrait of such approximations. Applications to the coherent states dynamics, small amplitude vibrations and collective rotations, show tha...

This paper proposes a new variational bound optimization framework for incorporating spatial prior information to the mean shift-based data-driven mode analysis, offering flexible control of the mean shift convergence. Two forms of Gaussian spatial priors are considered. Attractive prior pulls the convergence toward a desired location. Repulsive prior pushes away from such a location. Using a g...

NAVSYS Corporation has developed a prototype for a flexible, high-performance Space-based Software GPS Receiver (SSGR) to demonstrate the next generation of tracking and navigation capabilities for space applications. Based on a Software Defined Radio (SDR) approach, the SSGR will provide an integrated precision navigation and attitude determination solution for space applications. In order to ...

This paper addresses the problem of sampling from binary distributions with constraints. In particular, it proposes an MCMC method to draw samples from a distribution of the set of all states at a specified distance from some reference state. For example, when the reference state is the vector of zeros, the algorithm can draw samples from a binary distribution with a constraint on the number of...