scholarly journals Predator-Prey Systems in Pest Management

1991 ◽  
Vol 20 (1) ◽  
pp. 15-23 ◽  
Author(s):  
Carolyn R. Harper
Keyword(s):  
Decision Making ◽  
Decision Rules ◽  
Optimal Decision ◽  
Bioeconomic Model ◽  
Biological Modeling ◽  
Primary Target ◽  
Predator Prey ◽  
Prey System ◽  
Key Species ◽  
Chemical Pesticides

The use of chemical pesticides frequently causes minor pests to become serious problems by disturbing the natural controls that keep them in check. As a result, it is possible to suffer heavier crop losses after pesticides are introduced than before their introduction. Efficient use of pesticides requires complete biological modeling that takes the appropriate predator-prey relationships into account. A bioeconomic model is introduced involving three key species: a primary target pest, a secondary pest, and a natural enemy of the secondary pest. Optimal decision rules are derived and contrasted with myopic decision making, which treats the predator-prey system as an externality. The issue of resistance in the secondary pest is examined briefly.

Has Dynamic Programming Improved Decision Making?

2019 ◽  
Vol 11 (1) ◽  
pp. 833-858 ◽  
Author(s):  
John Rust
Keyword(s):  
Decision Making ◽  
Dynamic Programming ◽  
Real World ◽  
Operations Research ◽  
Decision Rules ◽  
Decision Problems ◽  
Optimal Decision ◽  
Sequential Decision ◽  
Success Stories ◽  
Real World Applications

Dynamic programming (DP) is a powerful tool for solving a wide class of sequential decision-making problems under uncertainty. In principle, it enables us to compute optimal decision rules that specify the best possible decision in any situation. This article reviews developments in DP and contrasts its revolutionary impact on economics, operations research, engineering, and artificial intelligence with the comparative paucity of its real-world applications to improve the decision making of individuals and firms. The fuzziness of many real-world decision problems and the difficulty in mathematically modeling them are key obstacles to a wider application of DP in real-world settings. Nevertheless, I discuss several success stories, and I conclude that DP offers substantial promise for improving decision making if we let go of the empirically untenable assumption of unbounded rationality and confront the challenging decision problems faced every day by individuals and firms.

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