Affiliation:
1. Lab 10, Department of Chemical Engineering, IISc Bangalore , Bangalore 560012, Karnataka, India
Abstract
Intelligent agents collect and process information from their dynamically evolving neighborhood to efficiently navigate through it. However, agent-level intelligence does not guarantee that at the level of a collective; a common example is the jamming we observe in traffic flows. In this study, we ask: how and when do the interactions between intelligent agents translate to desirable or intelligent collective outcomes? To explore this question, we choose a collective consisting of two kinds of agents with opposing desired directions of movement. Agents in this collective are minimally intelligent: they possess only a single facet of intelligence, viz., memory, where the agents remember how well they were able to travel in their desired directions and make up for their non-optimal past. We find that dynamics due to the agent’s memory influences the collective, giving rise to diverse outcomes at the level of the group: from those that are undesirable to those that can be called “intelligent.” When memory is short term, local rearrangement of agents leads to the formation of symmetrically jammed arrangements that take longer to unjam. However, when agents remember across longer time-scales, their dynamics become sensitive to small differences in their movement history. This gives rise to heterogeneity in the movement that causes agents to unjam more readily and form lanes.
Funder
DST INSPIRE faculty award
Subject
Applied Mathematics,General Physics and Astronomy,Mathematical Physics,Statistical and Nonlinear Physics