| Paper ID | D4-S6-T3.1 |
| Paper Title |
Continuous Random Variable Estimation is not Optimal for the Witsenhausen Counterexample |
| Authors |
Maël Le Treust, CNRS ETIS, France; Tobias Oechtering, KTH Royal Institute of Technology, Sweden |
| Session |
D4-S6-T3: Decentralized Estimation & Control |
| Chaired Session: |
Thursday, 15 July, 23:40 - 00:00 |
| Engagement Session: |
Friday, 16 July, 00:00 - 00:20 |
| Abstract |
Optimal design of distributed decision policies can be a difficult task, illustrated by the famous Witsenhausen counterexample. In this paper we characterize the optimal control designs for the vector-valued setting assuming that it results in an interim state, i.e. the result of the first decision maker action, that can be described by a continuous random variable which has a probability density function. More specifically, we provide a genie-aided outer bound that relies on our previous results for empirical coordination problems. This solution turns out to be not optimal in general, since it consists of a time-sharing strategy between two linear schemes of specific power. It follows that the optimal decision strategy for the original scalar Witsenhausen problem must lead to an interim state that cannot be described by a continuous random variable which has a probability density function.
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