  The sustainable foraging problem is a dynamic environment testbed for
exploring the forms of agent cognition in dealing with social dilemmas in a
multi-agent setting. The agents need to resist the temptation of individual
rewards through foraging and choose the collective long-term goal of
sustainability. We investigate methods of online learning in Neuro-Evolution
and Deep Recurrent Q-Networks to enable agents to attempt the problem one-shot
as is often required by wicked social problems. We further explore if learning
temporal dependencies with Long Short-Term Memory may be able to aid the agents
in developing sustainable foraging strategies in the long term. It was found
that the integration of Long Short-Term Memory assisted agents in developing
sustainable strategies for a single agent, however failed to assist agents in
managing the social dilemma that arises in the multi-agent scenario.
