Applying Probabilistic Programming to Affective Computing, Desmond Ong, Harold Soh ★, Jamil Zaki and Noah Goodman, IEEE Transactions on Affective Computing, 2019
Links: Paper | Github

This is joint work with the amazing Desmond Ong, Jamil Zaki and Noah Goodman

Affective Computing is a rapidly growing field spurred by advancements in artificial intelligence, but often, held back by the inability to translate psychological theories of emotion into tractable computational models.

To address this, we propose a probabilistic programming approach to affective computing, which models psychological-grounded theories as generative models of emotion, and implements them as stochastic, executable computer programs. We first review probabilistic approaches that integrate reasoning about emotions with reasoning about other latent mental states (e.g., beliefs, desires) in context. Recently-developed probabilistic programming languages offer several key desidarata over previous approaches, such as: (i) flexibility in representing emotions and emotional processes; (ii) modularity and compositionality; (iii) integration with deep learning libraries that facilitate efficient inference and learning from large, naturalistic data; and (iv) ease of adoption. Furthermore, using a probabilistic programming framework allows a standardized platform for theory-building and experimentation: Competing theories (e.g., of appraisal or other emotional processes) can be easily compared via modular substitution of code followed by model comparison.

To jumpstart adoption, we illustrate our points with executable code that researchers can easily modify for their own models. We end with a discussion of applications and future directions of the probabilistic programming approach.


You can find the paper here. Check out the repository on Github


Please consider citing our paper if you build upon our results and ideas.

Desmond Ong, Harold Soh ★, Jamil Zaki and Noah Goodman, “Applying Probabilistic Programming to Affective Computing”, IEEE Transactions on Affective Computing, 2019

title={Applying Probabilistic Programming to Affective Computing},
author={Ong, Desmond and Soh, Harold and Zaki, Jamil and Goodman, Noah},
journal={IEEE Transactions on Affective Computing},
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