Planning agents often lack the computational resources needed to build full planning trees for their environments. Agent designers commonly overcome this finite-horizon approximation by applying an evaluation function at the leaf-states of the planning tree. Recent work has proposed an alternative approach for overcoming computational constraints on agent design: modify the reward function. In ...

For decision-theoretic planning problems with an indefinite horizon, plan execution terminates after a finite number of steps with probability one, but the number of steps until termination (i.e., the horizon) is uncertain and unbounded. In the traditional approach to modeling such problems, called a stochastic shortest-path problem, plan execution terminates when a particular state is reached,...

We consider the planning of production over the infinite horizon in a system with timevarying convex production and inventory holding costs. This production lot size problem is frequently faced in industry where a forecast of future demand must be made and production is to be scheduled based on the forecast. Because forecasts of the future are costly and difficult to validate, a firm would like...

We investigate the computability of infinite-horizon partially observable Markov decision processes under discounted and undiscounted optimality criteria. The undecidability of the emptiness problem for probabilistic finite automata is used to show that a few technical problems, such as the isolation of a threshold, and closely related undiscounted problems such as probabilistic planning are un...

tendency to optimization in last decades has resulted in creating multi-product manufacturing systems. production planning in such systems is difficult, because optimal production volume that is calculated must be consistent with limitation of production system. hence, integration has been proposed to decide about these problems concurrently. main problem in integration is how we can relate pro...

We give necessary and sufficient conditions for finite detection of an optimal initial decision for infinite horizon optimization under a broad set of assumptions and provide an algorithm that is guaranteed to solve every solvable problem under these assumptions. We illustrate the theory and algorithms developed with applications in production planning and equipment replacement.

In this paper, we consider a class of single-item dynamic lot-sizing problem with quantity discount cost structure. We present an optimal polynomial algorithm for the case of multibreakpoint Ni, i = 1,2, . . . ,m. The complexity of our algorithm is O(n3 + mn2), where n is the number of periods in finite planning horizon.

In this paper, an inventory replenishment model for deteriorating items is developed. Demand for the item varies with time over a finite planning horizon, during which shortages are allowed and are completely back-ordered. The objective is to determine a replenishment policy that minimizes the total inventory cost. A search procedure based on Genetic Algorithm (GA) is presented and illustrated ...

In this paper we review a number of algorithms to compute Nash equilibria in deterministic linear quadratic differential games. We will review the open-loop and feedback information case. In both cases we address both the finite and the infinite-planning horizon.