We present necessary and sufficient conditions for discrete infinite horizon optimization problems with unique solutions to be solvable. These problems can be equivalently viewed as the task of finding a shortest path in an infinite directed network. We provide general forward algorithms with stopping rules for their solution. The key condition required is that of weak reachability, which roughly requires that for any sequence of nodes or states, it must be possible from optimal states to reach states close in cost to states along this sequence. Moreover the costs to reach these states must converge to zero. Applications are considered in optimal search, undiscounted Markov decision processes, and deterministic infinite horizon optimization...
Many real world problems with time-varying characteristic and unbounded horizon can be modeled as an...
http://deepblue.lib.umich.edu/bitstream/2027.42/7457/5/ban1366.0001.001.pdfhttp://deepblue.lib.umich...
With infinite horizon, optimal rules for sequential search from a known distribution feature a const...
Infinite horizon sequential decision problems may be solved by identifying a solution horizon, a fin...
We give necessary and sufficient conditions for finite detection of an optimal initial decision for ...
We give necessary and sucient conditions for finite detection of an optimal initial decision for inf...
Infinite-horizon non-stationary Markov decision processes provide a general framework to model many ...
Infinite-horizon non-stationary Markov decision processes provide a general framework to model many ...
The long term may be difficult to define. In the computer industry, looking months ahead may be far-...
We consider sequential decision problems over an infinite horizon. The forecast or solution horizon ...
We consider sequential decision problems over an infinite horizon. The forecast or solution horizon ...
We consider the problem of selecting an optimality criterion, when total costs diverge, in determini...
AbstractMonotonicity of optimal solutions to finite horizon dynamic optimization problems is used to...
We consider the stochastic infinite horizon optimization problem which seeks to minimize average cos...
Many real world problems with time-varying characteristic and unbounded horizon can be modeled as an...
Many real world problems with time-varying characteristic and unbounded horizon can be modeled as an...
http://deepblue.lib.umich.edu/bitstream/2027.42/7457/5/ban1366.0001.001.pdfhttp://deepblue.lib.umich...
With infinite horizon, optimal rules for sequential search from a known distribution feature a const...
Infinite horizon sequential decision problems may be solved by identifying a solution horizon, a fin...
We give necessary and sufficient conditions for finite detection of an optimal initial decision for ...
We give necessary and sucient conditions for finite detection of an optimal initial decision for inf...
Infinite-horizon non-stationary Markov decision processes provide a general framework to model many ...
Infinite-horizon non-stationary Markov decision processes provide a general framework to model many ...
The long term may be difficult to define. In the computer industry, looking months ahead may be far-...
We consider sequential decision problems over an infinite horizon. The forecast or solution horizon ...
We consider sequential decision problems over an infinite horizon. The forecast or solution horizon ...
We consider the problem of selecting an optimality criterion, when total costs diverge, in determini...
AbstractMonotonicity of optimal solutions to finite horizon dynamic optimization problems is used to...
We consider the stochastic infinite horizon optimization problem which seeks to minimize average cos...
Many real world problems with time-varying characteristic and unbounded horizon can be modeled as an...
Many real world problems with time-varying characteristic and unbounded horizon can be modeled as an...
http://deepblue.lib.umich.edu/bitstream/2027.42/7457/5/ban1366.0001.001.pdfhttp://deepblue.lib.umich...
With infinite horizon, optimal rules for sequential search from a known distribution feature a const...