Super-performance: sampling, planning, and ecological information

TL;DR

This paper explores the concepts of supersamplers and superplanners in naturalistic behavior, analyzing their coevolution, tradeoffs, and implications for human augmentation through ecological and cognitive modeling.

Contribution

It introduces the categories of supersamplers and superplanners, discusses their evolutionary relationships, and applies ecological information theory to understand their roles in perception and planning.

Findings

Supersamplers sample sensory information at high rates, exemplified by flies and frogs.

Superplanners internally store environmental information to evaluate multiple features.

Tradeoffs exist between sampling and planning capacities, with potential for relativistic regimes.

Abstract

The connection between active perception and the limits of performance provide a path to understanding naturalistic behavior. We can take a comparative cognitive modeling perspective to understand the limits of this performance and the existence of superperformance. We will discuss two categories that are hypothesized to originate in terms of coevolutionary relationships and evolutionary trade offs: supersamplers and superplanners. Supersamplers take snapshots of their sensory world at a very high sampling rate. Examples include flies (vision) and frogs (audition) with ecological specializations. Superplanners internally store information to evaluate and act upon multiple features of spatiotemporal environments. Slow lorises and turtles provide examples of superplanning capabilities. The Gibsonian Information (GI) paradigm is used to evaluate sensory sampling and planning with respect to direct perception and its role in capturing environmental information content. By contrast, superplanners utilize internal models of the environment to compensate for normal rates of sensory sampling, and this relationship often exists as a sampling/planning tradeoff. Supersamplers and superplanners can exist in adversarial relationships, or longer-term as coevolutionary relationships. Moreover, the tradeoff between sampling and planning capacity can break down, providing relativistic regimes. We can apply the principles of superperformance to human augmentation technologies.