We propose a meta-heuristic approach for solving nonlinear dynamic tracking games. In contrast to more "traditional" methods based on linear-quadratic (LQ) techniques, this derivative-free method is very flexible (e.g. to introduce inequality constraints). The meta-heuristic is applied to a...

NK models are agent-based simulations of market evolution generated through new entry and firm innovation, and are often focused on better understanding complex interdependencies in organizational phenomena. We provide a counterpoint to the mostly optimistic descriptions of the advantages and of...

We study a stochastic dynamic game of process innovation in which firms can initiate and terminate R&D efforts and production at different times. We discern the impact of knowledge spillovers on the investments in existing markets, as well as on the likely structure of newly forming markets, for...

Previous results on infinitely repeated agency do not allow income smoothing because it generates interdependence across time periods and private information for managers. Propositions 1-2 and Theorem show how to use dynamic programming to solve the agency problem. By using dynamic programming,...

This paper treats the risk-averse optimal portfolio problem with consumption in continuous time with a stochastic-volatility, jump-diffusion (SVJD) model of the underlying risky asset and the volatility. The new developments are the use of the SVJD model with double-uniform jump-amplitude...

An applied compact introductory survey of Markov stochastic processes and control in continuous time is presented. The presentation is in tutorial stages, beginning with deterministic dynamical systems for contrast and continuing on to perturbing the deterministic model with diffusions using...

We use minority game model to investigate evolutionary dynamics in complex networks of adaptive agents competing for limited resources. We show that the dynamics and the associated phase structures critically depend on the underlying network organizations, and evolution is a key mechanism for...

An optimum of a Markov decision process (MDP) is said to be myopic if it can be specified by solving a series of static problems. We identify new classes of MDPs with myopic optima and sequential games with myopic equilibrium points. In one of the classes the single-period reward is homogeneous...

Given an arbitrary black-box strategy for the Iterated Prisoner's Dilemma game, it is often difficult to gauge to which extent it can be exploited by other strategies. In the presence of imperfect public monitoring and resulting observation errors, deriving a theoretical solution is even more...