Social Cognitive Maps, Swarm Perception and Distributed Search on Dynamic Landscapes

TL;DR

This paper explores how swarm intelligence and social cognitive maps enable collective adaptation and problem solving in dynamic environments through self-organization, stigmergy, and feedback mechanisms, demonstrated with mathematical landscape models.

Contribution

It introduces a model combining social cognitive maps with swarm perception to study distributed search and adaptation in changing landscapes, highlighting the role of environmental feedback.

Findings

Collective intelligence adapts quickly to unforeseen changes.

Swarm perception enhances distributed search efficiency.

The model demonstrates adaptation to conflicting goals in dynamic landscapes.

Abstract

Swarm Intelligence (SI) is the property of a system whereby the collective behaviors of (unsophisticated) entities interacting locally with their environment cause coherent functional global patterns to emerge. SI provides a basis with which it is possible to explore collective (or distributed) problem solving without centralized control or the provision of a global model. To tackle the formation of a coherent social collective intelligence from individual behaviors, we discuss several concepts related to self-organization, stigmergy and social foraging in animals. Then, in a more abstract level we suggest and stress the role played not only by the environmental media as a driving force for societal learning, as well as by positive and negative feedbacks produced by the many interactions among agents. Finally, presenting a simple model based on the above features, we will address the collective adaptation of a social community to a cultural (environmental, contextual) or media informational dynamical landscape, represented here - for the purpose of different experiments - by several three-dimensional mathematical functions that suddenly change over time. Results indicate that the collective intelligence is able to cope and quickly adapt to unforeseen situations even when over the same cooperative foraging period, the community is requested to deal with two different and contradictory purposes. KEYWORDS: Swarm Intelligence and Perception, Social Cognitive Maps, Social Foraging, Self-Organization, Distributed Search and Optimization