Summary of Free Energy in a Circumplex Model Of Emotion, by Candice Pattisapu et al.
Free Energy in a Circumplex Model of Emotion
by Candice Pattisapu, Tim Verbelen, Riddhi J. Pitliya, Alex B. Kiefer, Mahault Albarracin
First submitted to arxiv on: 2 Jul 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: None
GrooveSquid.com Paper Summaries
GrooveSquid.com’s goal is to make artificial intelligence research accessible by summarizing AI papers in simpler terms. Each summary below covers the same AI paper, written at different levels of difficulty. The medium difficulty and low difficulty versions are original summaries written by GrooveSquid.com, while the high difficulty version is the paper’s original abstract. Feel free to learn from the version that suits you best!
| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary A novel approach to modeling emotions is proposed in this paper, building upon previous active inference accounts. The researchers introduce a Circumplex Model of emotion, which represents emotions as multi-dimensional along a spectrum of valence and arousal. This framework enables the derivation of valence and arousal signals from an agent’s expected free energy, with arousal linked to posterior belief entropy and valence tied to utility minus expected utility. Simulations of artificial agents engaged in a search task demonstrate how manipulation of priors and object presence can produce intuitive variability in emotional states. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This research paper explores new ways to understand emotions. It suggests that emotions are not just good or bad, but also have different levels of excitement or calmness. The scientists create a special model that shows how these different emotions can be connected to the amount of uncertainty or surprise an agent feels. They use this model to simulate artificial agents searching for objects and find that by changing the agents’ beliefs about what might happen, they can make the agents feel more excited or calmer. |
Keywords
» Artificial intelligence » Inference
