The overall aim of our work is to develop a generic adaptive control architecture for autonomous intelligent agents. In our previous work we showed how a single agent's survival can benefit from autobiographic memory. In the current work we extend this work by introducing a multi-agent context. Also, we investigate autobiographic agents which are able to share episodic memories (sequences of perceptions and actions) in the form of 'communications' with others in order to find necessary resources for 'surviving' in an environment. This Artificial Life perspective allows assessment of the potential benefits of such communications in a multi-agent context. A virtual experimental-based approach deals with different conditions on agent communications. Extending our previous work, we introduce an improved control architectures design for autobiographic agents that allows them to communicate episodic memories. Using detailed measurements of the agents' lifespan, this is compared both with groups of purely reactive agents and non-communicative autobiographic agents. Results confirm our previous research hypothesis that autobiographic memory can prove beneficial, indicating increases in the lifespan of an autonomous, autobiographic, minimal agent. The paper presents results from simulation runs varying the following parameters: a) with/without communications of episodic memories, b) varying the number of agents in the environment from one to five, and c) communications under different types of conditions, including presence/absence of costs and motivations. Results show that in experiments with certain numbers of agents, communicating memories with others can compensate for the negative effect of generally decreasing lifespan due to multiple agent interference. Experiments on specific combinations of motivation and cost conditions also show that, when cost is incurred for communication, agents perform better if they communicate memories only when they are in need of a resource.
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