Minimizing Regret ((FREE))

Minimizing Regret ((FREE))

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I decided to take the Regret Minimization Framework one step further and think about how my 80-year-old self would look back on the decisions I made with my time, and how I can alter my habits and activities to minimize future regret.

So what will your last words be And who will be in the room to hear them Remember how short and fragile life is. As difficult as this is to think about and say, some of you reading this email right now will not be here next year. Make every moment count with your family. Take a moment now to ponder 10 ways to minimize your regrets at the end of your life.

A wise man has the ability to visualize outcomes before they occur. Never make decisions from a self-centered perspective. Self-centered decisions often will grant you short-term gain but create long-term damage for you and everyone around you. Always hedge your bets toward the wise thing to do. You will have fewer regrets.

An important problem in sequential decision-making under uncertainty is to use limited data to compute a safe policy, i.e., a policy that is guaranteed to perform at least as well as a given baseline strategy. In this paper, we develop and analyze a new model-based approach to compute a safe policy when we have access to an inaccurate dynamics model of the system with known accuracy guarantees. Our proposed robust method uses this (inaccurate) model to directly minimize the (negative) regret w.r.t. the baseline policy. Contrary to the existing approaches, minimizing the regret allows one to improve the baseline policy in states with accurate dynamics and seamlessly fall back to the baseline policy, otherwise. We show that our formulation is NP-hard and propose an approximate algorithm. Our empirical results on several domains show that even this relatively simple approximate algorithm can significantl