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→Active inference and optimal decision (game) theory 主动推理与最优决策（博弈）理论
[[Optimal decision]] problems (usually formulated as [[partially observable Markov decision process]]es) are treated within active inference by absorbing [[Utility| utility functions]] into prior beliefs. In this setting, states that have a high utility (low cost) are states an agent expects to occupy. By equipping the generative model with hidden states that model control, policies (control sequences) that minimise variational free energy lead to high utility states.<ref>Friston, K., Samothrakis, S. & Montague, R., (2012). [http://www.fil.ion.ucl.ac.uk/~karl/Active%20inference%20and%20agency%20optimal%20control%20without%20cost%20functions.pdf Active inference and agency: optimal control without cost functions]. Biol. Cybernetics, 106(8–9), 523–41.</ref>
[[Optimal decision]] problems (usually formulated as [[partially observable Markov decision process]]es) are treated within active inference by absorbing [[Utility| utility functions]] into prior beliefs. In this setting, states that have a high utility (low cost) are states an agent expects to occupy. By equipping the generative model with hidden states that model control, policies (control sequences) that minimise variational free energy lead to high utility states.<ref>Friston, K., Samothrakis, S. & Montague, R., (2012). [http://www.fil.ion.ucl.ac.uk/~karl/Active%20inference%20and%20agency%20optimal%20control%20without%20cost%20functions.pdf Active inference and agency: optimal control without cost functions]. Biol. Cybernetics, 106(8–9), 523–41.</ref>
[[最优决策]]问题（通常表示为[[部分可观测马尔可夫决策过程]]es）通过将[[效用|效用函数]]吸收到先验信念中，在主动推理中处理。在此设置中，具有高效用（低成本）的状态是代理希望占用的状态。通过给生成模型配备模型控制的隐藏状态，最小化可变自由能的策略（控制序列）会导致高效用状态。 <ref>Friston, K., Samothrakis, S. & Montague, R., (2012). [http://www.fil.ion.ucl.ac.uk/~karl/Active%20inference%20and%20agency%20optimal%20control%20without%20cost%20functions.pdf Active inference and agency: optimal control without cost functions]. Biol. Cybernetics, 106(8–9), 523–41.</ref>
Neurobiologically, neuromodulators like [[dopamine]] are considered to report the precision of prediction errors by modulating the gain of principal cells encoding prediction error.<ref name="Friston_a">Friston, K. J. Shiner T, FitzGerald T, Galea JM, Adams R, Brown H, Dolan RJ, Moran R, Stephan KE, Bestmann S. (2012). [http://www.fil.ion.ucl.ac.uk/~karl/Dopamine%20Affordance%20and%20Active%20Inference.pdf Dopamine, affordance and active inference]. PLoS Comput. Biol., 8(1), p. e1002327.</ref> This is closely related to – but formally distinct from – the role of dopamine in reporting prediction errors ''per se''<ref>Fiorillo, C. D., Tobler, P. N. & Schultz, W., (2003). [http://e.guigon.free.fr/rsc/article/FiorilloEtAl03.pdf Discrete coding of reward probability and uncertainty by dopamine neurons]. Science, 299(5614), 1898–902.</ref> and related computational accounts.<ref>Frank, M. J., (2005). [http://ski.cog.brown.edu/papers/Frank_JOCN.pdf Dynamic dopamine modulation in the basal ganglia: a neurocomputational account of cognitive deficits in medicated and nonmedicated Parkinsonism]. J Cogn Neurosci., Jan, 1, 51–72.</ref>
Neurobiologically, neuromodulators like [[dopamine]] are considered to report the precision of prediction errors by modulating the gain of principal cells encoding prediction error.<ref name="Friston_a">Friston, K. J. Shiner T, FitzGerald T, Galea JM, Adams R, Brown H, Dolan RJ, Moran R, Stephan KE, Bestmann S. (2012). [http://www.fil.ion.ucl.ac.uk/~karl/Dopamine%20Affordance%20and%20Active%20Inference.pdf Dopamine, affordance and active inference]. PLoS Comput. Biol., 8(1), p. e1002327.</ref> This is closely related to – but formally distinct from – the role of dopamine in reporting prediction errors ''per se''<ref>Fiorillo, C. D., Tobler, P. N. & Schultz, W., (2003). [http://e.guigon.free.fr/rsc/article/FiorilloEtAl03.pdf Discrete coding of reward probability and uncertainty by dopamine neurons]. Science, 299(5614), 1898–902.</ref> and related computational accounts.<ref>Frank, M. J., (2005). [http://ski.cog.brown.edu/papers/Frank_JOCN.pdf Dynamic dopamine modulation in the basal ganglia: a neurocomputational account of cognitive deficits in medicated and nonmedicated Parkinsonism]. J Cogn Neurosci., Jan, 1, 51–72.</ref>
神经生物学上，神经调节剂[[多巴胺]]被认为通过调节编码预测误差的主细胞的增益来报告预测误差的准确性。<ref name="Friston_a">Friston, K. J. Shiner T, FitzGerald T, Galea JM, Adams R, Brown H, Dolan RJ, Moran R, Stephan KE, Bestmann S. (2012). [http://www.fil.ion.ucl.ac.uk/~karl/Dopamine%20Affordance%20and%20Active%20Inference.pdf Dopamine, affordance and active inference]. PLoS Comput. Biol., 8(1), p. e1002327.</ref> 这与多巴胺在报告预测错误“本身”中的作用密切相关，但在形式上与之不同<ref>Fiorillo, C. D., Tobler, P. N. & Schultz, W., (2003). [http://e.guigon.free.fr/rsc/article/FiorilloEtAl03.pdf Discrete coding of reward probability and uncertainty by dopamine neurons]. Science, 299(5614), 1898–902.</ref>以及与计算账户相关<ref>Frank, M. J., (2005). [http://ski.cog.brown.edu/papers/Frank_JOCN.pdf Dynamic dopamine modulation in the basal ganglia: a neurocomputational account of cognitive deficits in medicated and nonmedicated Parkinsonism]. J Cogn Neurosci., Jan, 1, 51–72.</ref>
=== Active inference and cognitive neuroscience 主动推理与认知神经科学===
=== Active inference and cognitive neuroscience 主动推理与认知神经科学===