Discounted MDP's: distribution functions and exponential utility maximization
SIAM Journal on Control and Optimization
An analysis of stochastic shortest path problems
Mathematics of Operations Research
Markov Decision Processes: Discrete Stochastic Dynamic Programming
Markov Decision Processes: Discrete Stochastic Dynamic Programming
MICAI '08 Proceedings of the 7th Mexican International Conference on Artificial Intelligence: Advances in Artificial Intelligence
Decision-theoretic planning with non-Markovian rewards
Journal of Artificial Intelligence Research
Planning under risk and Knightian uncertainty
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Planning and acting in partially observable stochastic domains
Artificial Intelligence
Percentile Optimization for Markov Decision Processes with Parameter Uncertainty
Operations Research
Brief On terminating Markov decision processes with a risk-averse objective function
Automatica (Journal of IFAC)
Risk-sensitive policies for sustainable renewable resource allocation
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Three
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In an environment of uncertainty where decisions must be taken, how to make a decision considering the risk? The shortest stochastic path (SSP) problem models the problem of reaching a goal with the least cost. However under uncertainty, a best decision may: minimize expected cost, minimize variance, minimize worst case, maximize best case, etc. Markov Decision Processes (MDPs) defines optimal decision in the shortest stochastic path problem as the decision that minimizes expected cost, therefore MDPs does not care about the risk. An extension of MDP which has few works in Artificial Intelligence literature is Risk Sensitive MDP. RSMDPs considers the risk and integrates expected cost, variance, worst case and best case in a simple way. We show theoretically the differences and similarities between MDPs and RSMDPs for modeling the SSP problem, in special the relationship between the discount factor γ and risk prone attitudes under the SSP with constant cost. We also exemplify each model in a simple artificial scenario.