SimGuide: Typed Multi-Context User Representations for Preference-Conditioned Agent Planning
Agents that act on a user's behalf must plan differently for different users, and increasingly do so from some structured representation of user context and not from raw interaction history. How much that structure is worth, and which parts of it carry the value, is largely unmeasured. We introduce SimBench, 47 preference-conditioned planning tasks over 9 synthetic users represented as 28 typed, potentially conflicting context blocks, where the correct plan depends on which contexts are active and how their conflicts are resolved. Against it we evaluate SimGuide, a framework combining typed multi-context representation, explicit conflict arbitration, and optional procedural grounding of i...
| Authors | Chirag Shah |
|---|---|
| Primary category | cs.AI |
| Published | 14 May 2026 |
| Last updated at source | 29 August 2026 |
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