Towards a Quantitative Understanding of Agency

Dear Colleagues,

The concept of an agent as an individualized entity that can act and has goals is an abstraction from living organisms that also encompasses robots and virtual creatures. This Special Issue will focus on novel approaches to understand the foundations of agency and individuality at the interface between biology and computer science, including extensions of the following lines of research:

• Formal classifications of agent–environment interactions as seen from an external observer—including the notions of non-trivial informational closure, autonomy, morphological computation, relevant information, stochastic thermodynamics with feedback, and semantic information.
• Measures used by Bayesian or reinforcement learning agents to internally guide their behaviour—including intrinsic motivation, active inference, empowerment, and predictive information maximization. 
• Classification of the dynamics of the physical components of an agent (e.g., Integrated Information Theory).
• Identification of entities that constitute agents within a larger dynamical system (e.g., informational individuality and complete local integration).

Additionally, special consideration will be given to (i) efforts trying to elucidate the relationships between these various perspectives, (ii) attempts trying to formalize the role of internal modeling and “imagination,” and (iii) extensions related to novel quantitative tools such as Partial Information Decomposition or causal emergence.

Dr. Ryota Kanai
Dr. Pablo A. Morales
Dr. Fernando E. Rosas
Guest Editors

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