How to build an information gathering and processing system: Lessons from naturally and artificially intelligent systems

Abstract

Imagine a situation in which you had to design a physical agent that could collect information from its environment, then store and process that information to help it respond appropriately to novel situations. What kinds of information should it attend to? How should the information be represented so as to allow efficient use and re-use? What kinds of constraints and trade-offs would there be? There are no unique answers. In this paper, we discuss some of the ways in which the need to be able to address problems of varying kinds and complexity can be met by different information processing systems. We also discuss different ways in which relevant information can be obtained, and how different kinds of information can be processed and used, by both biological organisms and artificial agents. We analyse several constraints and design features, and show how they relate both to biological organisms, and to lessons that can be learned from building artificial systems. Our standpoint overlaps with Karmiloff-Smith (1992) in that we assume that a collection of mechanisms geared to learning and developing in biological environments are available in forms that constrain, but do not determine, what can or will be learnt by individuals.

Explorative Learning and Functional Inferences on a Five-Step Means-Means-End Problem in Goffin’s Cockatoos (Cacatua goffini)

“…Nevertheless, our study also highlights the importance of parsimony in the interpretation of physical cognition results. The main challenge of cognitive research is to map the processes by which animals gather and use information to come up with innovative solutions to novel problems [32–34], and this is not achieved by invoking mentalistic concepts as explanations for complex behaviour. Dissecting the subjects’ performance to expose their path towards the solution and their response to task modifications can be productive; even extraordinary demonstrations of innovative capacity are not proof of the involvement of high-level mental faculties, and conversely, high levels of cognition could be involved in seemingly simple tasks.…”

Salient Features and Snapshots in Time: An Interdisciplinary Perspective on Object Representation

“…These properties allow a link to form between the agent and the environment. We will now consider what some of these primordial properties might be (see also [13]). …”