paper:doi-10-1016-j-tics-2012-08-006Planning as inference
Related work— refs + corpus + external arXiv
Cited / in-corpus / arXiv badges show which signals surfaced each row. Multi-source rows weighted higher.
- On Predictive planning and counterfactual learning in active inferenceTakuya Isomura, Adeel Razi Aswin Paul2024≈ 76%
- Modeling Human Inference of Others' Intentions in Complex Situations with Plan Predictability BiasSeiji Yamada Ryo Nakahashi2019≈ 76%
- A Unified View of Algorithms for Path Planning Using Probabilistic Inference on Factor GraphsFrancesco A.N. Palmieri and Krishna R. Pattipati and Giovanni Di Gennaro and Giovanni Fioretti and Francesco Verolla and Amedeo Buonanno2021≈ 74%
- ≈ 74%
- Active inference for action-unaware agentsKeisuke Suzuki, Ryota Kanai, Manuel Baltieri Filippo Torresan2025≈ 73%
- Active Inference or Control as Inference? A Unifying ViewAbraham Imohiosen, Jan Peters Joe Watson2020≈ 73%
- ≈ 73%
- Learning Perception and Planning with Deep Active InferenceTim Verbelen, Johannes Nauta, Cedric De Boom and Bart Dhoedt Ozan \c{C}atal2020≈ 73%
- Nested Reasoning About Autonomous Agents Using Probabilistic ProgramsJan-Willem van de Meent, David Wingate Iris Rubi Seaman2020≈ 73%
- ≈ 72%
- ≈ 72%
- Active inference and artificial reasoningLancelot Da Costa, Alexander Tschantz, Conor Heins, Christopher Buckley, Tim Verbelen, Thomas Parr Karl Friston2025≈ 72%
- Integrating cognitive map learning and active inference for planning in ambiguous environmentsBart Dhoedt, Tim Verbelen, Giovanni Pezzulo Toon Van de Maele2023≈ 72%
- On Solving a Stochastic Shortest-Path Markov Decision Process as Probabilistic InferenceBruno Lacerda, Paul Duckworth, Nick Hawes Mohamed Baioumy2021≈ 72%
- Interactive inference: a multi-agent model of cooperative joint actionsFrancesco Donnarumma, Giovanni Pezzulo Domenico Maisto2024≈ 71%
- ≈ 67%
- Active Inference, Curiosity and Insightin corpus2017≈ 66%
- ≈ 65%
- ≈ 64%
- Simulators — LessWrongin corpus≈ 64%
- Active inference: demystified and comparedin corpus2021≈ 64%
- When Thinking LLMs Lie: Unveiling the Strategic Deception in Representations of Reasoning Modelsin corpus2025≈ 63%
- ≈ 63%
- ≈ 63%
- Active Inference: A Process Theoryin corpus2017≈ 63%
- ≈ 62%
- ≈ 62%
- Cognitive glues are shared models of relative scarcities: the economics of collective intelligencein corpus2026≈ 62%
- ≈ 61%
- The biogenic approach to cognitionin corpus2005≈ 61%
Similar preprints — Semantic Scholar
Cited by (4)
- Active Inference, Curiosity and Insight
Minimizing expected variational free energy under a discrete-state Markov decision process generative model is sufficient to produce curiosity, epistemic learning, and insight without any additional m
- Active inference: demystified and compared
Active inference agents operating under expected free energy minimization achieve 98.90 [98.00, 99.79] average score in a non-stationary FrozenLake OpenAI gym environment, compared to 64.39 [60.33, 68
- Active Inference: A Process Theory
A single variational principle—minimizing variational free energy via gradient descent on a Markov decision process (MDP) generative model—is sufficient to derive neuronal dynamics that reproduce, wit
- Active inference on discrete state-spaces: a synthesis
Active inference on discrete state-spaces, formalized as partially observable Markov decision processes (POMDPs) with likelihood matrix A, transition matrix B, and prior D, unifies perception, plannin