Memory shapes time perception and intertemporal choices
This work addresses the problem of understanding time perception and decision-making biases for researchers in psychology and AI, but it is incremental as it builds on existing theories by applying information theory and AI techniques.
The study tackled the problem of explaining temporal distortions and intertemporal choice preferences by showing they arise from coding efficiency in sensorimotor representations, with results indicating that interactions constraining future behavior are perceived as longer and more valuable, and that memory constraints lead to different discount functions like exponential and hyperbolic discounting.
There is a consensus that human and non-human subjects experience temporal distortions in many stages of their perceptual and decision-making systems. Similarly, intertemporal choice research has shown that decision-makers undervalue future outcomes relative to immediate ones. Here we combine techniques from information theory and artificial intelligence to show how both temporal distortions and intertemporal choice preferences can be explained as a consequence of the coding efficiency of sensorimotor representation. In particular, the model implies that interactions that constrain future behavior are perceived as being both longer in duration and more valuable. Furthermore, using simulations of artificial agents, we investigate how memory constraints enforce a renormalization of the perceived timescales. Our results show that qualitatively different discount functions, such as exponential and hyperbolic discounting, arise as a consequence of an agent's probabilistic model of the world.