Living organisms or artificial entities such as human organizations face the trade-offs of exploration and exploitation. Exploration is about seeking new knowledge and information, acquiring new skills whereas exploitation is about taking advantage of existing resources, knowledge and skills. Too much exploration could be detrimental to achievement of short-term goals e.g. survival, but too much exploitation could be detrimental to long-term success. This agent-based model explores the relationship between persistence with local exploration under varying conditions of resource distribution (random, uniform, or concentrated) and change in availability of resources over time (declining, steady or growing) and varying cost of relocation (from low to high). Results of the simulation experiment indicate that when resources are concentrated and are not declining i.e. either remain fixed or grow over time, there was a negative relationship between persistence and resources acquired (wealth) i.e. it always made sense to quit local exploration sooner and cast a wider net. When resources were concentrated but were declining over time, when moving cost increased, persistence continued to have a positive relationship with resources acquired (wealth) i.e. waiting instead of quitting paid off. When there was no moving cost, persistence did not pay off. When resources were concentrated and when the resources were not declining i.e. either remain fixed or growing over time, there was a negative relationship between persistence and resources acquired (wealth) i.e. it always made sense to quit local exploration sooner and cast a wider net.
When resources were either randomly distributed or uniformly distributed but were declining over time, when moving cost increased, persistence had a positive relationship with resources acquired (wealth). When there was no moving cost or low moving cost, persistence did not pay off.
Model url: https://www.comses.net/codebases/78b5ff6c-80e2-443e-8049-cfabed23813a/releases/1.0.0/