# Target Tracking for Contextual Bandits: Application to Demand Side Management

arXiv: https://arxiv.org/abs/1901.09532 · HTML: https://mlsanity.com/paper/1901.09532/

## Key facts

- Cited by 6 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 28 Jan 2019.

## Built on by (most cited first, 6 of 6)

- [ESCADA: Efficient Safety and Context Aware Dose Allocation for Precision Medicine](https://mlsanity.com/paper/2111.13415/) (2021)
- [Towards Efficient and Optimal Covariance-Adaptive Algorithms for Combinatorial Semi-Bandits](https://mlsanity.com/paper/2402.15171/) (2024)
- [Reimagining Demand-Side Management with Mean Field Learning](https://mlsanity.com/paper/2302.08190/) (2023)
- [A Direct Approach for Handling Contextual Bandits with Latent State Dynamics](https://mlsanity.com/paper/2604.08149/) (2026)
- [Bandits for Efficient Experimentation: Adapting to Control Group, Preferences, and Context Drifts](https://mlsanity.com/paper/2606.09802/) (2026)
- [Learning-Based Decision Making for Combustion Phasing Control in Multi-Fuel CI Engines with Latent Fuel Reactivity Estimation](https://mlsanity.com/paper/2606.18393/) (2026)

## Abstract (arXiv)

We propose a contextual-bandit approach for demand side management by offering price incentives. More precisely, a target mean consumption is set at each round and the mean consumption is modeled as a complex function of the distribution of prices sent and of some contextual variables such as the temperature, weather, and so on. The performance of our strategies is measured in quadratic losses through a regret criterion. We offer T2/3 upper bounds on this regret (up to poly-logarithmic terms)---and even faster rates under stronger assumptions---for strategies inspired by standard strategies for contextual bandits (like LinUCB, see Li et al., 2010). Simulations on a real data set gathered by UK Power Networks, in which price incentives were offered, show that our strategies are effective and may indeed manage demand response by suitably picking the price levels.