Modeling the Emergence of Proto-Cognition

The emergence of cognition marks a great evolutionary transition in the behavior of living systems. Whereas before, organisms’ survival depended on their genetic pre-dispositions, cognition allowed them to alter their decision-making process as a consequence of their learning and development. We do not yet know how this transition to cognition occurred, and what underlying principles were responsible for it.


This project will develop in several stages. First, we will develop models of agents that self-assemble in an artificial chemistry. We will quantify the information flow between the agents and their environments, and study the structure of these interactions. Next, we will study the interaction among multiple agents put in a same environment. We will quantify the information flows between these individuals, and the integrated behavior of the resulting social system. Finally, we will identify conditions in which agents construct a network of social interactions that help them learn adaptive behavior throughout their lifetime.

Solving the theoretical challenges of developing this model will deepen our understanding of cognition and how it emerged. By demonstrating the emergence of minimal forms of cognition in a computational model, we plan to provide a foundation for a theory that can later be generalized to more complex classes of cognition, allowing us to build cognitive robots or extend the cognition of real living systems.

1. Ben-Jacob, Eshel, Inon Cohen, and Herbert Levine (2000) Cooperative Self-Organization of Microorganisms. Advances in Physics, 49.4: 395-554.
2. Fernando, Chrisantha Thomas, Eors Szathmary, and Phil Husbands (2012). Selectionist and Evolutionary Approaches to Brain Function: A Critical Appraisal. Frontiers in Computational Neuroscience, 6: 24.
3. Watson, Richard A. et al. (2015). Evolutionary Connectionism: Algorithmic Principles Underlying the Evolution of Biological Organisation in Evo-Devo, Evo-Eco and Evolutionary Transitions. Evolutionary Biology.
4. Michael S.C. Thomas and James L. McClelland (2008). Connectionist Models of Cognition. The Cambridge Handbook of Computational Psychology, 23-58.


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