Planning and Acting in Partially Observable Stochastic Domains.

Kaelbling, L. P., Littman, M. L., & Cassandra, A. R. (1998). Planning and Acting in Partially Observable Stochastic Domains. Artificial Intelligence, 101(1), 1-2.

Type

Journal article

Intellectual base

Primary research

Year

1998

Volume

101

Issue

1

Pages

1-2

ISSN

0004-3702

DOI

10.1016/s0004-3702(98)00023-x

DOI registrant

Elsevier

Link

https://doi.org/10.1016/S0004-3702(98)00023-X

Cited from

cognitive_science

Cited by

2 citations across 2 artifacts.

Each citation links to the sentence it supports in the citing article.

Primes

• Theory Of Mind
  • AI and language models: planning agents, dialogue systems, and language models that must model what a user knows, does not know, or believes incorrectly use belief-state tracking in MDPs/POMDPs and multi-agent RL.

    This sourceFoundational treatment of belief-state tracking in POMDPs, the formal apparatus by which agents model hidden state for planning.

Domain-specific

• Partially observable Markov decision process
  • The entry records a descriptive analytical identity; practical use requires the governing domain's evidence, standards, and safety obligations.

Verification

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