SAPIENT
- Type
- Research
- Year
- 2025
- Status
- active
A conversational recommendation system that combines a learned agent with Monte Carlo tree search for multi-turn planning.
SAPIENT pairs a conversational agent with a planner that explores future dialogue actions through Monte Carlo tree search. The selected plans supervise the conversational agent, creating an iterative self-training loop.
The release includes code and data for evaluating strategic, non-myopic recommendation conversations, plus an efficiency-oriented SAPIENT-e variant.