Dynamic Programming and Optimal Control
Dynamic Programming and Optimal Control
Introduction to Reinforcement Learning
Introduction to Reinforcement Learning
Convex Optimization
Self-Organizing Agents for Efficient Sustainable Resource Utilization
WI-IAT '12 Proceedings of the The 2012 IEEE/WIC/ACM International Joint Conferences on Web Intelligence and Intelligent Agent Technology - Volume 02
Shortest stochastic path with risk sensitive evaluation
MICAI'12 Proceedings of the 11th Mexican international conference on Advances in Artificial Intelligence - Volume Part I
| Hi-index | 0.00 |
Markov Decision Processes arise as a natural model for many renewable resources allocation problems. In many such problems, high stakes decisions with potentially catastrophic outcomes (such as the collapse of an entire ecosystem) need to be taken by carefully balancing social, economic, and ecologic goals. We introduce a broad class of such MDP models with a risk averse attitude of the decision maker, in order to obtain policies that are more balanced with respect to the welfare of future generations. We prove that they admit a closed form solution that can be efficiently computed. We show an application of the proposed framework to the Pacific Halibut marine fishery, obtaining new and more cautious policies. Our results strengthen findings of related policies from the literature by providing new evidence that a policy based on periodic closures of the fishery should be employed, in place of the one traditionally used that harvests a constant proportion of the stock every year.