Principles of Synthetic Intelligence: Psi: An Architecture of Motivated Cognition

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What can the brain teach us about building artificial intelligence? (2016, neutral): “[rBML] Bach, J. (2009) Principles of synthetic intelligence.”
Artificial General Intelligence: Concept, State of the Art, and Future Prospects (2009, methodology): “…the LIDA diagram as given in prior papers by Stan Franklin, Bernard Baars and colleagues (Baars and Franklin, 2009; Figure 3, modeling motivation and action selection, is a lightly modiﬁed version of the Psi diagram from Joscha Bach’s book Principles of Synthetic Intelligence (Bach, 2009).”
Emerging social awareness: Exploring intrinsic motivation in multiagent learning (2011, methodology): “Domer further defines other social signals that facilitate social interactions: anti-l-signals that punish unsuccessful social interactions, and internal l-signals that reward socially-acceptable behaviors [21], [22].”
On Defining Artificial Intelligence (2019, background): “Such a project may take inspirations from psychology in its architecture or mechanisms (Newell, 1990; Franklin, 2007; Bach, 2009), or use psychological data to train a machine learning model to replicate the behavior (Flach, 2012).”