Equation 6 · The Hardest Unsolved Problems in AI Agent Architecture
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A useful decomposition for what an agent needs to track is the belief it holds over the true state of its task, updated as new observations arrive. In the classical formalism, if b(s) is the agent’s probability distribution over possible states before an observation, a is the action just taken, o is the observation that followed, T is the environment’s transition model and O its observation model, the updated belief is
Sources cited in the article section
- [4] Planning and Acting in Partially Observable Stochastic Domains ↗
- [5] MemGPT: Towards LLMs as Operating Systems ↗
- [6] Compaction ↗
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