Cognitive World Model for Progressive BDI/E Trajectory Evaluation of Conversational Agents
As LLM-based conversational agents advance toward increasingly open-ended and interaction-intensive scenarios, task completion alone provides an incomplete assessment of their effectiveness. The evolution of users' internal states, including beliefs, desires, intentions, and emotions (BDI/E), serves as an intermediate signal connecting agent behaviors with interaction outcomes and reflects how conversational strategies shape users during multi-turn interactions. However, existing evaluation paradigms primarily focus on surface-level responses or final outcomes, providing limited insight into the underlying cognitive processes. This limitation makes it difficult to diagnose why agents succ...
| Authors | Minghui Ma, Bin Guo, Hao Wang et al. |
|---|---|
| Primary category | cs.AI |
| Published | 28 June 2026 |
| Last updated at source | 31 July 2026 |
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